metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: multilabel_classification
results: []
multilabel_classification
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: 0.1275
- F1 Micro: 0.8546
- F1 Macro: 0.5865
- Accuracy: 0.9780
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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 255 | 0.2939 | 0.8282 | 0.5696 | 0.9604 |
| 0.7587 | 2.0 | 510 | 0.1965 | 0.8546 | 0.5865 | 0.9780 |
| 0.7587 | 3.0 | 765 | 0.1275 | 0.8546 | 0.5865 | 0.9780 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2