|
|
--- |
|
|
base_model: mistralai/Mistral-7B-v0.1 |
|
|
library_name: peft |
|
|
license: apache-2.0 |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: Mistral_Task2_semantic_pred |
|
|
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. --> |
|
|
|
|
|
# Mistral_Task2_semantic_pred |
|
|
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.2310 |
|
|
- Accuracy: 0.7327 |
|
|
- Precision: 0.7327 |
|
|
- Recall: 0.7327 |
|
|
- F1 score: 0.7327 |
|
|
|
|
|
## 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: 16 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 5 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score | |
|
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
|
|
| 1.0308 | 0.5208 | 200 | 0.9212 | 0.7014 | 0.7014 | 0.7014 | 0.7014 | |
|
|
| 0.6176 | 1.0417 | 400 | 0.9613 | 0.6884 | 0.6884 | 0.6884 | 0.6884 | |
|
|
| 0.3639 | 1.5625 | 600 | 1.6970 | 0.6089 | 0.6089 | 0.6089 | 0.6089 | |
|
|
| 0.3578 | 2.0833 | 800 | 1.4605 | 0.6219 | 0.6219 | 0.6219 | 0.6219 | |
|
|
| 0.2448 | 2.6042 | 1000 | 0.8444 | 0.7419 | 0.7419 | 0.7419 | 0.7419 | |
|
|
| 0.2156 | 3.125 | 1200 | 1.0639 | 0.7171 | 0.7171 | 0.7171 | 0.7171 | |
|
|
| 0.1641 | 3.6458 | 1400 | 1.3295 | 0.7132 | 0.7132 | 0.7132 | 0.7132 | |
|
|
| 0.1687 | 4.1667 | 1600 | 0.8896 | 0.7731 | 0.7731 | 0.7731 | 0.7731 | |
|
|
| 0.1074 | 4.6875 | 1800 | 1.2310 | 0.7327 | 0.7327 | 0.7327 | 0.7327 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.12.0 |
|
|
- Transformers 4.44.2 |
|
|
- Pytorch 2.4.0+cu121 |
|
|
- Datasets 2.21.0 |
|
|
- Tokenizers 0.19.1 |
