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
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Model tree for Lduignan1/croissantllm_alector
Base model
croissantllm/CroissantLLMChat-v0.1