Instructions to use kk-aivio/189cee1c-0270-4877-8909-95d7c74d62fe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/189cee1c-0270-4877-8909-95d7c74d62fe with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "kk-aivio/189cee1c-0270-4877-8909-95d7c74d62fe") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 80792096
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:02dbc6ebb26dd9878c174fe474685e1e92441b44de1f783961e0e2d2fb17c107
|
| 3 |
size 80792096
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 41459700
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:afd6f1963e7f5af41c48aaebf553890456a04369650c66ce5eb390b5894575ca
|
| 3 |
size 41459700
|
last-checkpoint/rng_state.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 14244
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d9adb5ee314935bca3f91975cefb6876b6e167fb77efc10175a88c35427783ff
|
| 3 |
size 14244
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1064
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bb578e75c11a81e85dda67a691f96ba4793a02960f1409fd3e1511aac873491a
|
| 3 |
size 1064
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,9 +1,9 @@
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
-
"epoch": 0.
|
| 5 |
"eval_steps": 3,
|
| 6 |
-
"global_step":
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
@@ -102,6 +102,13 @@
|
|
| 102 |
"eval_samples_per_second": 23.805,
|
| 103 |
"eval_steps_per_second": 11.915,
|
| 104 |
"step": 9
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 105 |
}
|
| 106 |
],
|
| 107 |
"logging_steps": 1,
|
|
@@ -116,12 +123,12 @@
|
|
| 116 |
"should_evaluate": false,
|
| 117 |
"should_log": false,
|
| 118 |
"should_save": true,
|
| 119 |
-
"should_training_stop":
|
| 120 |
},
|
| 121 |
"attributes": {}
|
| 122 |
}
|
| 123 |
},
|
| 124 |
-
"total_flos":
|
| 125 |
"train_batch_size": 2,
|
| 126 |
"trial_name": null,
|
| 127 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 0.004235044997353097,
|
| 5 |
"eval_steps": 3,
|
| 6 |
+
"global_step": 10,
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
|
|
| 102 |
"eval_samples_per_second": 23.805,
|
| 103 |
"eval_steps_per_second": 11.915,
|
| 104 |
"step": 9
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.004235044997353097,
|
| 108 |
+
"grad_norm": 0.37966233491897583,
|
| 109 |
+
"learning_rate": 0.0002,
|
| 110 |
+
"loss": 1.532,
|
| 111 |
+
"step": 10
|
| 112 |
}
|
| 113 |
],
|
| 114 |
"logging_steps": 1,
|
|
|
|
| 123 |
"should_evaluate": false,
|
| 124 |
"should_log": false,
|
| 125 |
"should_save": true,
|
| 126 |
+
"should_training_stop": true
|
| 127 |
},
|
| 128 |
"attributes": {}
|
| 129 |
}
|
| 130 |
},
|
| 131 |
+
"total_flos": 2744651772592128.0,
|
| 132 |
"train_batch_size": 2,
|
| 133 |
"trial_name": null,
|
| 134 |
"trial_params": null
|