3b3fa2d5-5b01-4479-9447-d2c53d0f40b6

This model is a fine-tuned version of JackFram/llama-68m on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.6811

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: 0.000206
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 50
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0001	1	5.5038
3.408	0.0042	50	3.4438
3.0626	0.0084	100	2.9485
2.8832	0.0127	150	2.9219
2.8748	0.0169	200	2.8083
2.9119	0.0211	250	2.8442
2.6523	0.0253	300	2.7347
2.7253	0.0295	350	2.7128
2.5942	0.0338	400	2.7093
2.72	0.0380	450	2.6901
3.0129	0.0422	500	2.6811

Framework versions

• PEFT 0.13.2
• Transformers 4.46.0
• Pytorch 2.5.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1