|
|
--- |
|
|
base_model: mistralai/Mistral-7B-Instruct-v0.2 |
|
|
datasets: |
|
|
- generator |
|
|
library_name: peft |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- trl |
|
|
- sft |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: Mistral_Sentiment_Classification_2024-08-19 |
|
|
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_Sentiment_Classification_2024-08-19 |
|
|
|
|
|
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1144 |
|
|
|
|
|
## 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: 2.5e-05 |
|
|
- train_batch_size: 1 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 2 |
|
|
- num_epochs: 5 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:-----:|:---------------:| |
|
|
| 0.1264 | 0.2048 | 500 | 0.1188 | |
|
|
| 0.1096 | 0.4097 | 1000 | 0.1146 | |
|
|
| 0.1289 | 0.6145 | 1500 | 0.1123 | |
|
|
| 0.1089 | 0.8193 | 2000 | 0.1106 | |
|
|
| 0.1218 | 1.0242 | 2500 | 0.1083 | |
|
|
| 0.0987 | 1.2290 | 3000 | 0.1079 | |
|
|
| 0.1074 | 1.4338 | 3500 | 0.1069 | |
|
|
| 0.0906 | 1.6387 | 4000 | 0.1062 | |
|
|
| 0.1094 | 1.8435 | 4500 | 0.1053 | |
|
|
| 0.0951 | 2.0483 | 5000 | 0.1068 | |
|
|
| 0.1 | 2.2532 | 5500 | 0.1068 | |
|
|
| 0.0799 | 2.4580 | 6000 | 0.1062 | |
|
|
| 0.0767 | 2.6628 | 6500 | 0.1058 | |
|
|
| 0.1046 | 2.8677 | 7000 | 0.1054 | |
|
|
| 0.0727 | 3.0725 | 7500 | 0.1091 | |
|
|
| 0.0737 | 3.2773 | 8000 | 0.1092 | |
|
|
| 0.0967 | 3.4822 | 8500 | 0.1092 | |
|
|
| 0.0726 | 3.6870 | 9000 | 0.1091 | |
|
|
| 0.0909 | 3.8918 | 9500 | 0.1085 | |
|
|
| 0.074 | 4.0967 | 10000 | 0.1141 | |
|
|
| 0.0777 | 4.3015 | 10500 | 0.1143 | |
|
|
| 0.0695 | 4.5063 | 11000 | 0.1145 | |
|
|
| 0.0604 | 4.7112 | 11500 | 0.1142 | |
|
|
| 0.0612 | 4.9160 | 12000 | 0.1144 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.12.0 |
|
|
- Transformers 4.44.0 |
|
|
- Pytorch 2.4.0+cu121 |
|
|
- Datasets 2.21.0 |
|
|
- Tokenizers 0.19.1 |
