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---
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 |