checkpoints

This model is a fine-tuned version of mozilla/distilvit on an unknown dataset. It achieves the following results on the evaluation set:

• Gen Len: 10.6487
• Loss: 0.1739
• Meteor: 0.4120
• Rouge1: 50.0916
• Rouge2: 24.7223
• Rougel: 46.9416
• Rougelsum: 46.9372

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 100
• eval_batch_size: 100
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Gen Len	Validation Loss	Meteor	Rouge1	Rouge2	Rougel	Rougelsum
No log	0.3891	100	10.4163	0.1764	0.4117	50.0198	24.6331	46.9071	46.8907
No log	0.7782	200	10.6487	0.1739	0.4120	50.0916	24.7223	46.9416	46.9372

Framework versions

• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1