---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- generator
model-index:
- name: Mistral_Sentiment_Classification_2024-06-01
  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_2024-06-01

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: 0.2992

## 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: 0.03
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4525        | 0.1126 | 100  | 0.3376          |
| 0.3445        | 0.2252 | 200  | 0.3210          |
| 0.3244        | 0.3378 | 300  | 0.3147          |
| 0.3012        | 0.4505 | 400  | 0.3101          |
| 0.3169        | 0.5631 | 500  | 0.3069          |
| 0.3357        | 0.6757 | 600  | 0.3045          |
| 0.31          | 0.7883 | 700  | 0.3027          |
| 0.3146        | 0.9009 | 800  | 0.3008          |
| 0.2868        | 1.0135 | 900  | 0.2988          |
| 0.2881        | 1.1261 | 1000 | 0.2988          |
| 0.3123        | 1.2387 | 1100 | 0.2972          |
| 0.2796        | 1.3514 | 1200 | 0.2960          |
| 0.2865        | 1.4640 | 1300 | 0.2943          |
| 0.2906        | 1.5766 | 1400 | 0.2929          |
| 0.2713        | 1.6892 | 1500 | 0.2919          |
| 0.2751        | 1.8018 | 1600 | 0.2906          |
| 0.2916        | 1.9144 | 1700 | 0.2895          |
| 0.264         | 2.0270 | 1800 | 0.2917          |
| 0.2603        | 2.1396 | 1900 | 0.2919          |
| 0.2486        | 2.2523 | 2000 | 0.2917          |
| 0.2583        | 2.3649 | 2100 | 0.2910          |
| 0.2556        | 2.4775 | 2200 | 0.2905          |
| 0.2629        | 2.5901 | 2300 | 0.2897          |
| 0.2423        | 2.7027 | 2400 | 0.2894          |
| 0.256         | 2.8153 | 2500 | 0.2889          |
| 0.2664        | 2.9279 | 2600 | 0.2881          |
| 0.2595        | 3.0405 | 2700 | 0.2933          |
| 0.2297        | 3.1532 | 2800 | 0.2955          |
| 0.239         | 3.2658 | 2900 | 0.2940          |
| 0.2363        | 3.3784 | 3000 | 0.2929          |
| 0.2295        | 3.4910 | 3100 | 0.2937          |
| 0.2438        | 3.6036 | 3200 | 0.2923          |
| 0.2226        | 3.7162 | 3300 | 0.2920          |
| 0.2473        | 3.8288 | 3400 | 0.2924          |
| 0.2314        | 3.9414 | 3500 | 0.2919          |
| 0.2218        | 4.0541 | 3600 | 0.2985          |
| 0.218         | 4.1667 | 3700 | 0.2994          |
| 0.2154        | 4.2793 | 3800 | 0.2994          |
| 0.2032        | 4.3919 | 3900 | 0.2994          |
| 0.2234        | 4.5045 | 4000 | 0.2996          |
| 0.224         | 4.6171 | 4100 | 0.2995          |
| 0.1978        | 4.7297 | 4200 | 0.2997          |
| 0.2204        | 4.8423 | 4300 | 0.3000          |
| 0.2114        | 4.9550 | 4400 | 0.2992          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1