metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral-lora-token-classification
results: []
mistral-lora-token-classification
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0675
- Precision: 0.7504
- Recall: 0.6836
- F1-score: 0.7154
- Accuracy: 0.7676
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.3948 | 1.0 | 762 | 1.2063 | 0.7208 | 0.6344 | 0.6748 | 0.7387 |
| 0.8588 | 2.0 | 1524 | 1.1396 | 0.6313 | 0.8310 | 0.7175 | 0.7203 |
| 0.7512 | 3.0 | 2286 | 1.0329 | 0.7281 | 0.7404 | 0.7342 | 0.7708 |
| 0.6143 | 4.0 | 3048 | 1.0510 | 0.6917 | 0.7512 | 0.7202 | 0.7505 |
| 0.5564 | 5.0 | 3810 | 1.0675 | 0.7504 | 0.6836 | 0.7154 | 0.7676 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2