GaetanMichelet's picture
End of training
ac24265 verified
---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-2
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-2_60-samples_config-2
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-7B_task-2_60-samples_config-2
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co./mistralai/Mistral-7B-Instruct-v0.3) on the GaetanMichelet/chat-60_ft_task-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5370
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.9782 | 0.6957 | 2 | 0.9433 |
| 0.9325 | 1.7391 | 5 | 0.7483 |
| 0.657 | 2.7826 | 8 | 0.6180 |
| 0.5682 | 3.8261 | 11 | 0.5942 |
| 0.5483 | 4.8696 | 14 | 0.5666 |
| 0.4875 | 5.9130 | 17 | 0.5441 |
| 0.4347 | 6.9565 | 20 | 0.5370 |
| 0.3995 | 8.0 | 23 | 0.5381 |
| 0.3709 | 8.6957 | 25 | 0.5431 |
| 0.2801 | 9.7391 | 28 | 0.5705 |
| 0.2582 | 10.7826 | 31 | 0.6300 |
| 0.1682 | 11.8261 | 34 | 0.6605 |
| 0.1192 | 12.8696 | 37 | 0.7693 |
| 0.0549 | 13.9130 | 40 | 0.8641 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1