croissantllm_alector

This model is a fine-tuned version of croissantllm/CroissantLLMChat-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4429

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• training_steps: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.4674	1.4815	10	2.7493
2.3361	2.9630	20	1.7841
1.6418	4.4444	30	1.6253
1.5506	5.9259	40	1.5834
1.4118	7.4074	50	1.5230
1.3397	8.8889	60	1.5239
1.2705	10.3704	70	1.4704
1.181	11.8519	80	1.4517
1.1903	13.3333	90	1.4438
1.1721	14.8148	100	1.4429

Framework versions

• PEFT 0.10.0
• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1