| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: cllm-1.0.0 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # cllm-1.0.0 |
| |
|
| | This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.7403 |
| |
|
| | ## 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: 0.0003 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 8 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 64 |
| | - total_eval_batch_size: 8 |
| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 50 |
| | - num_epochs: 1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | No log | 0.0044 | 2000 | 3.8105 | |
| | | 4.2179 | 0.0089 | 4000 | 3.4461 | |
| | | 4.2179 | 0.0133 | 6000 | 3.2612 | |
| | | 3.2341 | 0.0178 | 8000 | 3.1610 | |
| | | 3.2341 | 0.0222 | 10000 | 3.0834 | |
| | | 3.0422 | 0.0267 | 12000 | 3.0260 | |
| | | 3.0422 | 0.0311 | 14000 | 2.9872 | |
| | | 2.9347 | 0.0356 | 16000 | 2.9444 | |
| | | 2.9347 | 0.0400 | 18000 | 2.9090 | |
| | | 2.874 | 0.0445 | 20000 | 2.8854 | |
| | | 2.874 | 0.0489 | 22000 | 2.8585 | |
| | | 2.8204 | 0.0534 | 24000 | 2.8405 | |
| | | 2.8204 | 0.0578 | 26000 | 2.8245 | |
| | | 2.7825 | 0.0622 | 28000 | 2.8106 | |
| | | 2.7825 | 0.0667 | 30000 | 2.7993 | |
| | | 2.7555 | 0.0711 | 32000 | 2.7867 | |
| | | 2.7555 | 0.0756 | 34000 | 2.7738 | |
| | | 2.7285 | 0.0800 | 36000 | 2.7700 | |
| | | 2.7285 | 0.0845 | 38000 | 2.7597 | |
| | | 2.7179 | 0.0889 | 40000 | 2.7591 | |
| | | 2.7179 | 0.0934 | 42000 | 2.7488 | |
| | | 2.7119 | 0.0978 | 44000 | 2.7512 | |
| | | 2.7119 | 0.1023 | 46000 | 2.7487 | |
| | | 2.7043 | 0.1067 | 48000 | 2.7436 | |
| | | 2.7043 | 0.1111 | 50000 | 2.7422 | |
| | | 2.7013 | 0.1156 | 52000 | 2.7435 | |
| | | 2.7013 | 0.1200 | 54000 | 2.7388 | |
| | | 2.7029 | 0.1245 | 56000 | 2.7380 | |
| | | 2.7029 | 0.1289 | 58000 | 2.7403 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.1 |
| | |
