metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral_Sparse_refined_web_relu_2024-03-11
results: []
Mistral_Sparse_refined_web_relu_2024-03-11
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4851
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 0
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 850
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 8.7876 | 0.0 | 25 | 8.7120 |
| 8.1837 | 0.01 | 50 | 8.1741 |
| 7.7529 | 0.01 | 75 | 7.8037 |
| 7.5336 | 0.02 | 100 | 7.6036 |
| 7.1718 | 0.02 | 125 | 7.1058 |
| 4.7663 | 0.02 | 150 | 4.7163 |
| 3.7548 | 0.03 | 175 | 3.8001 |
| 3.2625 | 0.03 | 200 | 3.4192 |
| 3.0886 | 0.04 | 225 | 3.2355 |
| 2.9928 | 0.04 | 250 | 3.1153 |
| 2.8555 | 0.04 | 275 | 3.0392 |
| 2.8289 | 0.05 | 300 | 2.9870 |
| 2.7933 | 0.05 | 325 | 2.9505 |
| 2.6073 | 0.06 | 350 | 2.9160 |
| 2.7488 | 0.06 | 375 | 2.8941 |
| 2.7795 | 0.06 | 400 | 2.8722 |
| 2.7317 | 0.07 | 425 | 2.8537 |
| 2.6982 | 0.07 | 450 | 2.8407 |
| 2.5823 | 0.08 | 475 | 2.8258 |
| 2.6419 | 0.08 | 500 | 2.8164 |
| 2.7195 | 0.08 | 525 | 2.8082 |
| 2.6239 | 0.09 | 550 | 2.7980 |
| 2.7273 | 0.09 | 575 | 2.7869 |
| 2.5436 | 0.1 | 600 | 2.7809 |
| 2.6159 | 0.1 | 625 | 2.7761 |
| 2.6563 | 0.1 | 650 | 2.7666 |
| 2.6728 | 0.11 | 675 | 2.7573 |
| 2.6047 | 0.11 | 700 | 2.7509 |
| 2.6237 | 0.12 | 725 | 2.7493 |
| 2.5305 | 0.12 | 750 | 2.7458 |
| 2.5329 | 0.12 | 775 | 2.7392 |
| 2.6538 | 0.13 | 800 | 2.7359 |
| 2.6079 | 0.13 | 825 | 2.7314 |
| 2.5927 | 0.14 | 850 | 2.7275 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0