Text Generation
Transformers
Safetensors
qwen2
Generated from Trainer
rl-swarm
grpo
gensyn
I am endangered gregarious wolf
trl
genrl-swarm
I am endangered_gregarious_wolf
conversational
text-generation-inference
Instructions to use Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf") model = AutoModelForCausalLM.from_pretrained("Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf
- SGLang
How to use Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf with Docker Model Runner:
docker model run hf.co/Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf
End of training
Browse files- README.md +1 -1
- all_results.json +5 -5
- model.safetensors +1 -1
- train_results.json +5 -5
- trainer_state.json +112 -112
- training_args.bin +1 -1
README.md
CHANGED
|
@@ -40,7 +40,7 @@ This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing
|
|
| 40 |
- TRL: 0.15.2
|
| 41 |
- Transformers: 4.51.3
|
| 42 |
- Pytorch: 2.5.1
|
| 43 |
-
- Datasets: 3.5.
|
| 44 |
- Tokenizers: 0.21.1
|
| 45 |
|
| 46 |
## Citations
|
|
|
|
| 40 |
- TRL: 0.15.2
|
| 41 |
- Transformers: 4.51.3
|
| 42 |
- Pytorch: 2.5.1
|
| 43 |
+
- Datasets: 3.5.1
|
| 44 |
- Tokenizers: 0.21.1
|
| 45 |
|
| 46 |
## Citations
|
all_results.json
CHANGED
|
@@ -1,8 +1,8 @@
|
|
| 1 |
{
|
| 2 |
"total_flos": 0.0,
|
| 3 |
-
"train_loss":
|
| 4 |
-
"train_runtime":
|
| 5 |
-
"train_samples":
|
| 6 |
-
"train_samples_per_second":
|
| 7 |
-
"train_steps_per_second": 0.
|
| 8 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"total_flos": 0.0,
|
| 3 |
+
"train_loss": 3.151223813802062e-06,
|
| 4 |
+
"train_runtime": 518.4281,
|
| 5 |
+
"train_samples": 84,
|
| 6 |
+
"train_samples_per_second": 0.617,
|
| 7 |
+
"train_steps_per_second": 0.039
|
| 8 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1976163472
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d9a701aeb54101ce4e42a9633ea798be4a0e3fe48627a8452bd09b42a9b7e3ae
|
| 3 |
size 1976163472
|
train_results.json
CHANGED
|
@@ -1,8 +1,8 @@
|
|
| 1 |
{
|
| 2 |
"total_flos": 0.0,
|
| 3 |
-
"train_loss":
|
| 4 |
-
"train_runtime":
|
| 5 |
-
"train_samples":
|
| 6 |
-
"train_samples_per_second":
|
| 7 |
-
"train_steps_per_second": 0.
|
| 8 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"total_flos": 0.0,
|
| 3 |
+
"train_loss": 3.151223813802062e-06,
|
| 4 |
+
"train_runtime": 518.4281,
|
| 5 |
+
"train_samples": 84,
|
| 6 |
+
"train_samples_per_second": 0.617,
|
| 7 |
+
"train_steps_per_second": 0.039
|
| 8 |
}
|
trainer_state.json
CHANGED
|
@@ -2,7 +2,7 @@
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
-
"epoch":
|
| 6 |
"eval_steps": 500,
|
| 7 |
"global_step": 20,
|
| 8 |
"is_hyper_param_search": false,
|
|
@@ -10,209 +10,209 @@
|
|
| 10 |
"is_world_process_zero": true,
|
| 11 |
"log_history": [
|
| 12 |
{
|
| 13 |
-
"completion_length":
|
| 14 |
-
"epoch": 0.
|
| 15 |
-
"grad_norm": 6.
|
| 16 |
"kl": 0.0,
|
| 17 |
"learning_rate": 5e-07,
|
| 18 |
-
"loss":
|
| 19 |
-
"reward": 1.
|
| 20 |
-
"reward_std": 1.
|
| 21 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 22 |
"rewards/consensus_reward_func": 0.0625,
|
| 23 |
"rewards/cumulative_reward_2": 0.0,
|
| 24 |
-
"rewards/final_correctness_reward_func": 0.
|
| 25 |
-
"rewards/question_recreation_reward_func": 0.
|
| 26 |
"rewards/soft_format_reward_func": 0.0,
|
| 27 |
-
"rewards/strict_format_reward_func": 0.
|
| 28 |
-
"rewards/xmlcount_reward_func": 0.
|
| 29 |
"step": 2
|
| 30 |
},
|
| 31 |
{
|
| 32 |
-
"completion_length":
|
| 33 |
-
"epoch":
|
| 34 |
-
"grad_norm":
|
| 35 |
-
"kl": 0.
|
| 36 |
"learning_rate": 4.864543104251586e-07,
|
| 37 |
"loss": 0.0,
|
| 38 |
-
"reward": 0.
|
| 39 |
-
"reward_std": 0.
|
| 40 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 41 |
-
"rewards/consensus_reward_func": 0.
|
| 42 |
"rewards/cumulative_reward_2": 0.0,
|
| 43 |
-
"rewards/final_correctness_reward_func": 0.
|
| 44 |
-
"rewards/question_recreation_reward_func": 0.
|
| 45 |
"rewards/soft_format_reward_func": 0.0,
|
| 46 |
"rewards/strict_format_reward_func": 0.0,
|
| 47 |
-
"rewards/xmlcount_reward_func": 0.
|
| 48 |
"step": 4
|
| 49 |
},
|
| 50 |
{
|
| 51 |
-
"completion_length":
|
| 52 |
-
"epoch":
|
| 53 |
-
"grad_norm":
|
| 54 |
-
"kl": 0.
|
| 55 |
"learning_rate": 4.472851273490984e-07,
|
| 56 |
"loss": 0.0,
|
| 57 |
-
"reward": 0.
|
| 58 |
-
"reward_std": 0.
|
| 59 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 60 |
-
"rewards/consensus_reward_func": 0.
|
| 61 |
"rewards/cumulative_reward_2": 0.0,
|
| 62 |
"rewards/final_correctness_reward_func": 0.0,
|
| 63 |
-
"rewards/question_recreation_reward_func": 0.
|
| 64 |
"rewards/soft_format_reward_func": 0.0,
|
| 65 |
"rewards/strict_format_reward_func": 0.0,
|
| 66 |
-
"rewards/xmlcount_reward_func": 0.
|
| 67 |
"step": 6
|
| 68 |
},
|
| 69 |
{
|
| 70 |
-
"completion_length":
|
| 71 |
-
"epoch":
|
| 72 |
-
"grad_norm":
|
| 73 |
-
"kl": 0.
|
| 74 |
"learning_rate": 3.867370395306068e-07,
|
| 75 |
"loss": 0.0,
|
| 76 |
-
"reward": 0.
|
| 77 |
-
"reward_std": 0.
|
| 78 |
"rewards/concensus_correctness_reward_func": 0.0,
|
| 79 |
-
"rewards/consensus_reward_func": 0.
|
| 80 |
"rewards/cumulative_reward_2": 0.0,
|
| 81 |
-
"rewards/final_correctness_reward_func": 0.
|
| 82 |
-
"rewards/question_recreation_reward_func": 0.
|
| 83 |
"rewards/soft_format_reward_func": 0.0,
|
| 84 |
"rewards/strict_format_reward_func": 0.0,
|
| 85 |
-
"rewards/xmlcount_reward_func":
|
| 86 |
"step": 8
|
| 87 |
},
|
| 88 |
{
|
| 89 |
-
"completion_length":
|
| 90 |
-
"epoch":
|
| 91 |
-
"grad_norm":
|
| 92 |
-
"kl": 0.
|
| 93 |
"learning_rate": 3.1137137178519977e-07,
|
| 94 |
"loss": 0.0,
|
| 95 |
-
"reward": 0.
|
| 96 |
-
"reward_std": 0.
|
| 97 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 98 |
-
"rewards/consensus_reward_func": 0.
|
| 99 |
"rewards/cumulative_reward_2": 0.0,
|
| 100 |
-
"rewards/final_correctness_reward_func": 0.
|
| 101 |
-
"rewards/question_recreation_reward_func": 0.
|
| 102 |
"rewards/soft_format_reward_func": 0.0,
|
| 103 |
"rewards/strict_format_reward_func": 0.0,
|
| 104 |
-
"rewards/xmlcount_reward_func": 0.
|
| 105 |
"step": 10
|
| 106 |
},
|
| 107 |
{
|
| 108 |
-
"completion_length":
|
| 109 |
-
"epoch":
|
| 110 |
-
"grad_norm":
|
| 111 |
-
"kl": 0.
|
| 112 |
"learning_rate": 2.2935516363191693e-07,
|
| 113 |
"loss": 0.0,
|
| 114 |
-
"reward": 0.
|
| 115 |
-
"reward_std": 0.
|
| 116 |
"rewards/concensus_correctness_reward_func": 0.0,
|
| 117 |
-
"rewards/consensus_reward_func": 0.
|
| 118 |
"rewards/cumulative_reward_2": 0.0,
|
| 119 |
"rewards/final_correctness_reward_func": 0.0,
|
| 120 |
-
"rewards/question_recreation_reward_func": 0.
|
| 121 |
"rewards/soft_format_reward_func": 0.0,
|
| 122 |
"rewards/strict_format_reward_func": 0.0,
|
| 123 |
-
"rewards/xmlcount_reward_func": 0.
|
| 124 |
"step": 12
|
| 125 |
},
|
| 126 |
{
|
| 127 |
-
"completion_length":
|
| 128 |
-
"epoch":
|
| 129 |
-
"grad_norm":
|
| 130 |
-
"kl": 0.
|
| 131 |
"learning_rate": 1.4957614383675767e-07,
|
| 132 |
"loss": 0.0,
|
| 133 |
-
"reward": 0.
|
| 134 |
-
"reward_std": 0.
|
| 135 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 136 |
"rewards/consensus_reward_func": 0.0,
|
| 137 |
"rewards/cumulative_reward_2": 0.0,
|
| 138 |
-
"rewards/final_correctness_reward_func": 0.
|
| 139 |
-
"rewards/question_recreation_reward_func": 0.
|
| 140 |
"rewards/soft_format_reward_func": 0.0,
|
| 141 |
"rewards/strict_format_reward_func": 0.0,
|
| 142 |
-
"rewards/xmlcount_reward_func":
|
| 143 |
"step": 14
|
| 144 |
},
|
| 145 |
{
|
| 146 |
-
"completion_length":
|
| 147 |
-
"epoch":
|
| 148 |
-
"grad_norm":
|
| 149 |
-
"kl": 0.
|
| 150 |
"learning_rate": 8.067960709356478e-08,
|
| 151 |
"loss": 0.0,
|
| 152 |
-
"reward": 0.
|
| 153 |
-
"reward_std": 0.
|
| 154 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 155 |
-
"rewards/consensus_reward_func": 0.
|
| 156 |
"rewards/cumulative_reward_2": 0.0,
|
| 157 |
-
"rewards/final_correctness_reward_func": 0.
|
| 158 |
-
"rewards/question_recreation_reward_func": 0.
|
| 159 |
"rewards/soft_format_reward_func": 0.0,
|
| 160 |
"rewards/strict_format_reward_func": 0.0,
|
| 161 |
-
"rewards/xmlcount_reward_func": 0.
|
| 162 |
"step": 16
|
| 163 |
},
|
| 164 |
{
|
| 165 |
-
"completion_length":
|
| 166 |
-
"epoch":
|
| 167 |
-
"grad_norm":
|
| 168 |
-
"kl": 0.
|
| 169 |
"learning_rate": 3.013156219837776e-08,
|
| 170 |
"loss": 0.0,
|
| 171 |
-
"reward":
|
| 172 |
-
"reward_std":
|
| 173 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 174 |
-
"rewards/consensus_reward_func": 0.
|
| 175 |
"rewards/cumulative_reward_2": 0.0,
|
| 176 |
-
"rewards/final_correctness_reward_func": 0.
|
| 177 |
-
"rewards/question_recreation_reward_func": 0.
|
| 178 |
"rewards/soft_format_reward_func": 0.0,
|
| 179 |
-
"rewards/strict_format_reward_func": 0.
|
| 180 |
-
"rewards/xmlcount_reward_func": 0.
|
| 181 |
"step": 18
|
| 182 |
},
|
| 183 |
{
|
| 184 |
-
"completion_length":
|
| 185 |
-
"epoch":
|
| 186 |
-
"grad_norm":
|
| 187 |
-
"kl": 0.
|
| 188 |
"learning_rate": 3.4096741493194193e-09,
|
| 189 |
"loss": 0.0,
|
| 190 |
-
"reward":
|
| 191 |
-
"reward_std": 1.
|
| 192 |
-
"rewards/concensus_correctness_reward_func": 0.
|
| 193 |
"rewards/consensus_reward_func": 0.25,
|
| 194 |
"rewards/cumulative_reward_2": 0.0,
|
| 195 |
-
"rewards/final_correctness_reward_func": 0.
|
| 196 |
-
"rewards/question_recreation_reward_func": 0.
|
| 197 |
"rewards/soft_format_reward_func": 0.0,
|
| 198 |
"rewards/strict_format_reward_func": 0.0,
|
| 199 |
-
"rewards/xmlcount_reward_func": 0.
|
| 200 |
"step": 20
|
| 201 |
},
|
| 202 |
{
|
| 203 |
-
"epoch":
|
| 204 |
"step": 20,
|
| 205 |
"total_flos": 0.0,
|
| 206 |
-
"train_loss":
|
| 207 |
-
"train_runtime":
|
| 208 |
-
"train_samples_per_second":
|
| 209 |
-
"train_steps_per_second": 0.
|
| 210 |
}
|
| 211 |
],
|
| 212 |
"logging_steps": 2,
|
| 213 |
"max_steps": 20,
|
| 214 |
"num_input_tokens_seen": 0,
|
| 215 |
-
"num_train_epochs":
|
| 216 |
"save_steps": 25,
|
| 217 |
"stateful_callbacks": {
|
| 218 |
"TrainerControl": {
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 1.8571428571428572,
|
| 6 |
"eval_steps": 500,
|
| 7 |
"global_step": 20,
|
| 8 |
"is_hyper_param_search": false,
|
|
|
|
| 10 |
"is_world_process_zero": true,
|
| 11 |
"log_history": [
|
| 12 |
{
|
| 13 |
+
"completion_length": 343.84375,
|
| 14 |
+
"epoch": 0.19047619047619047,
|
| 15 |
+
"grad_norm": 6.41450834274292,
|
| 16 |
"kl": 0.0,
|
| 17 |
"learning_rate": 5e-07,
|
| 18 |
+
"loss": 0.0,
|
| 19 |
+
"reward": 1.3421010066522285,
|
| 20 |
+
"reward_std": 1.406665334085119,
|
| 21 |
+
"rewards/concensus_correctness_reward_func": 0.6851250007748604,
|
| 22 |
"rewards/consensus_reward_func": 0.0625,
|
| 23 |
"rewards/cumulative_reward_2": 0.0,
|
| 24 |
+
"rewards/final_correctness_reward_func": 0.125,
|
| 25 |
+
"rewards/question_recreation_reward_func": 0.32650725438725203,
|
| 26 |
"rewards/soft_format_reward_func": 0.0,
|
| 27 |
+
"rewards/strict_format_reward_func": 0.015625,
|
| 28 |
+
"rewards/xmlcount_reward_func": 0.1273437519557774,
|
| 29 |
"step": 2
|
| 30 |
},
|
| 31 |
{
|
| 32 |
+
"completion_length": 339.53125,
|
| 33 |
+
"epoch": 0.38095238095238093,
|
| 34 |
+
"grad_norm": 6.3102498054504395,
|
| 35 |
+
"kl": 0.0012349215921858558,
|
| 36 |
"learning_rate": 4.864543104251586e-07,
|
| 37 |
"loss": 0.0,
|
| 38 |
+
"reward": 0.3265813000034541,
|
| 39 |
+
"reward_std": 0.4629429771230207,
|
| 40 |
+
"rewards/concensus_correctness_reward_func": 0.0,
|
| 41 |
+
"rewards/consensus_reward_func": 0.0625,
|
| 42 |
"rewards/cumulative_reward_2": 0.0,
|
| 43 |
+
"rewards/final_correctness_reward_func": 0.0625,
|
| 44 |
+
"rewards/question_recreation_reward_func": 0.13289380201604217,
|
| 45 |
"rewards/soft_format_reward_func": 0.0,
|
| 46 |
"rewards/strict_format_reward_func": 0.0,
|
| 47 |
+
"rewards/xmlcount_reward_func": 0.06868749670684338,
|
| 48 |
"step": 4
|
| 49 |
},
|
| 50 |
{
|
| 51 |
+
"completion_length": 296.1875,
|
| 52 |
+
"epoch": 0.5714285714285714,
|
| 53 |
+
"grad_norm": 61.84025573730469,
|
| 54 |
+
"kl": 0.005961592213679978,
|
| 55 |
"learning_rate": 4.472851273490984e-07,
|
| 56 |
"loss": 0.0,
|
| 57 |
+
"reward": 0.5405496190069243,
|
| 58 |
+
"reward_std": 0.5028865041094832,
|
| 59 |
+
"rewards/concensus_correctness_reward_func": 0.059812501072883606,
|
| 60 |
+
"rewards/consensus_reward_func": 0.125,
|
| 61 |
"rewards/cumulative_reward_2": 0.0,
|
| 62 |
"rewards/final_correctness_reward_func": 0.0,
|
| 63 |
+
"rewards/question_recreation_reward_func": 0.27689335064496845,
|
| 64 |
"rewards/soft_format_reward_func": 0.0,
|
| 65 |
"rewards/strict_format_reward_func": 0.0,
|
| 66 |
+
"rewards/xmlcount_reward_func": 0.07884375378489494,
|
| 67 |
"step": 6
|
| 68 |
},
|
| 69 |
{
|
| 70 |
+
"completion_length": 249.1875,
|
| 71 |
+
"epoch": 0.7619047619047619,
|
| 72 |
+
"grad_norm": 56.74770736694336,
|
| 73 |
+
"kl": 0.002046526838967111,
|
| 74 |
"learning_rate": 3.867370395306068e-07,
|
| 75 |
"loss": 0.0,
|
| 76 |
+
"reward": 0.37825396441621706,
|
| 77 |
+
"reward_std": 0.37752981589437695,
|
| 78 |
"rewards/concensus_correctness_reward_func": 0.0,
|
| 79 |
+
"rewards/consensus_reward_func": 0.0625,
|
| 80 |
"rewards/cumulative_reward_2": 0.0,
|
| 81 |
+
"rewards/final_correctness_reward_func": 0.0625,
|
| 82 |
+
"rewards/question_recreation_reward_func": 0.18716021499130875,
|
| 83 |
"rewards/soft_format_reward_func": 0.0,
|
| 84 |
"rewards/strict_format_reward_func": 0.0,
|
| 85 |
+
"rewards/xmlcount_reward_func": 0.06609375029802322,
|
| 86 |
"step": 8
|
| 87 |
},
|
| 88 |
{
|
| 89 |
+
"completion_length": 285.75,
|
| 90 |
+
"epoch": 0.9523809523809523,
|
| 91 |
+
"grad_norm": 35.71620178222656,
|
| 92 |
+
"kl": 0.0014948487314541126,
|
| 93 |
"learning_rate": 3.1137137178519977e-07,
|
| 94 |
"loss": 0.0,
|
| 95 |
+
"reward": 0.6967899320879951,
|
| 96 |
+
"reward_std": 0.5912124498172489,
|
| 97 |
+
"rewards/concensus_correctness_reward_func": 0.06024999916553497,
|
| 98 |
+
"rewards/consensus_reward_func": 0.125,
|
| 99 |
"rewards/cumulative_reward_2": 0.0,
|
| 100 |
+
"rewards/final_correctness_reward_func": 0.125,
|
| 101 |
+
"rewards/question_recreation_reward_func": 0.2623211840982549,
|
| 102 |
"rewards/soft_format_reward_func": 0.0,
|
| 103 |
"rewards/strict_format_reward_func": 0.0,
|
| 104 |
+
"rewards/xmlcount_reward_func": 0.12421874701976776,
|
| 105 |
"step": 10
|
| 106 |
},
|
| 107 |
{
|
| 108 |
+
"completion_length": 347.2916666666667,
|
| 109 |
+
"epoch": 1.0952380952380953,
|
| 110 |
+
"grad_norm": 5.5424346923828125,
|
| 111 |
+
"kl": 0.001293833294766955,
|
| 112 |
"learning_rate": 2.2935516363191693e-07,
|
| 113 |
"loss": 0.0,
|
| 114 |
+
"reward": 0.1296683083055541,
|
| 115 |
+
"reward_std": 0.42109029918598634,
|
| 116 |
"rewards/concensus_correctness_reward_func": 0.0,
|
| 117 |
+
"rewards/consensus_reward_func": 0.08333333333333333,
|
| 118 |
"rewards/cumulative_reward_2": 0.0,
|
| 119 |
"rewards/final_correctness_reward_func": 0.0,
|
| 120 |
+
"rewards/question_recreation_reward_func": 0.13004330720286816,
|
| 121 |
"rewards/soft_format_reward_func": 0.0,
|
| 122 |
"rewards/strict_format_reward_func": 0.0,
|
| 123 |
+
"rewards/xmlcount_reward_func": -0.08370832974712054,
|
| 124 |
"step": 12
|
| 125 |
},
|
| 126 |
{
|
| 127 |
+
"completion_length": 373.09375,
|
| 128 |
+
"epoch": 1.2857142857142856,
|
| 129 |
+
"grad_norm": 17.043167114257812,
|
| 130 |
+
"kl": 0.0012364095746306702,
|
| 131 |
"learning_rate": 1.4957614383675767e-07,
|
| 132 |
"loss": 0.0,
|
| 133 |
+
"reward": 0.3166529495501891,
|
| 134 |
+
"reward_std": 0.406706450904494,
|
| 135 |
+
"rewards/concensus_correctness_reward_func": 0.0,
|
| 136 |
"rewards/consensus_reward_func": 0.0,
|
| 137 |
"rewards/cumulative_reward_2": 0.0,
|
| 138 |
+
"rewards/final_correctness_reward_func": 0.0625,
|
| 139 |
+
"rewards/question_recreation_reward_func": 0.16937170409073588,
|
| 140 |
"rewards/soft_format_reward_func": 0.0,
|
| 141 |
"rewards/strict_format_reward_func": 0.0,
|
| 142 |
+
"rewards/xmlcount_reward_func": 0.08478125440888107,
|
| 143 |
"step": 14
|
| 144 |
},
|
| 145 |
{
|
| 146 |
+
"completion_length": 245.1875,
|
| 147 |
+
"epoch": 1.4761904761904763,
|
| 148 |
+
"grad_norm": 27.399072647094727,
|
| 149 |
+
"kl": 0.0028427706747606862,
|
| 150 |
"learning_rate": 8.067960709356478e-08,
|
| 151 |
"loss": 0.0,
|
| 152 |
+
"reward": 0.6848066907841712,
|
| 153 |
+
"reward_std": 0.6611888102197554,
|
| 154 |
+
"rewards/concensus_correctness_reward_func": 0.06012500077486038,
|
| 155 |
+
"rewards/consensus_reward_func": 0.125,
|
| 156 |
"rewards/cumulative_reward_2": 0.0,
|
| 157 |
+
"rewards/final_correctness_reward_func": 0.125,
|
| 158 |
+
"rewards/question_recreation_reward_func": 0.25196293997578323,
|
| 159 |
"rewards/soft_format_reward_func": 0.0,
|
| 160 |
"rewards/strict_format_reward_func": 0.0,
|
| 161 |
+
"rewards/xmlcount_reward_func": 0.12271874817088246,
|
| 162 |
"step": 16
|
| 163 |
},
|
| 164 |
{
|
| 165 |
+
"completion_length": 264.25,
|
| 166 |
+
"epoch": 1.6666666666666665,
|
| 167 |
+
"grad_norm": 42.305606842041016,
|
| 168 |
+
"kl": 0.0022985513096500654,
|
| 169 |
"learning_rate": 3.013156219837776e-08,
|
| 170 |
"loss": 0.0,
|
| 171 |
+
"reward": 1.2035528365522623,
|
| 172 |
+
"reward_std": 1.0453436647367198,
|
| 173 |
+
"rewards/concensus_correctness_reward_func": 0.15699999779462814,
|
| 174 |
+
"rewards/consensus_reward_func": 0.25,
|
| 175 |
"rewards/cumulative_reward_2": 0.0,
|
| 176 |
+
"rewards/final_correctness_reward_func": 0.1875,
|
| 177 |
+
"rewards/question_recreation_reward_func": 0.26874033408239484,
|
| 178 |
"rewards/soft_format_reward_func": 0.0,
|
| 179 |
+
"rewards/strict_format_reward_func": 0.015625,
|
| 180 |
+
"rewards/xmlcount_reward_func": 0.3246875018812716,
|
| 181 |
"step": 18
|
| 182 |
},
|
| 183 |
{
|
| 184 |
+
"completion_length": 378.5625,
|
| 185 |
+
"epoch": 1.8571428571428572,
|
| 186 |
+
"grad_norm": 64.05872344970703,
|
| 187 |
+
"kl": 0.013361819263081998,
|
| 188 |
"learning_rate": 3.4096741493194193e-09,
|
| 189 |
"loss": 0.0,
|
| 190 |
+
"reward": 0.8212161803094205,
|
| 191 |
+
"reward_std": 1.0907838449347764,
|
| 192 |
+
"rewards/concensus_correctness_reward_func": 0.06012500077486038,
|
| 193 |
"rewards/consensus_reward_func": 0.25,
|
| 194 |
"rewards/cumulative_reward_2": 0.0,
|
| 195 |
+
"rewards/final_correctness_reward_func": 0.1875,
|
| 196 |
+
"rewards/question_recreation_reward_func": 0.24912242317805067,
|
| 197 |
"rewards/soft_format_reward_func": 0.0,
|
| 198 |
"rewards/strict_format_reward_func": 0.0,
|
| 199 |
+
"rewards/xmlcount_reward_func": 0.07446875050663948,
|
| 200 |
"step": 20
|
| 201 |
},
|
| 202 |
{
|
| 203 |
+
"epoch": 1.8571428571428572,
|
| 204 |
"step": 20,
|
| 205 |
"total_flos": 0.0,
|
| 206 |
+
"train_loss": 3.151223813802062e-06,
|
| 207 |
+
"train_runtime": 518.4281,
|
| 208 |
+
"train_samples_per_second": 0.617,
|
| 209 |
+
"train_steps_per_second": 0.039
|
| 210 |
}
|
| 211 |
],
|
| 212 |
"logging_steps": 2,
|
| 213 |
"max_steps": 20,
|
| 214 |
"num_input_tokens_seen": 0,
|
| 215 |
+
"num_train_epochs": 2,
|
| 216 |
"save_steps": 25,
|
| 217 |
"stateful_callbacks": {
|
| 218 |
"TrainerControl": {
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5944
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:78268932364dfe195fcfba8eaf3212b6eedd2ad354c3defdcbbb8bcdd22dd702
|
| 3 |
size 5944
|