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---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-2
- GaetanMichelet/chat-120_ft_task-2
- GaetanMichelet/chat-180_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_180-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_180-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, the GaetanMichelet/chat-120_ft_task-2 and the GaetanMichelet/chat-180_ft_task-2 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.5403
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 0.8897 | 0.9412 | 8 | 0.8554 |
| 0.6578 | 2.0 | 17 | 0.6425 |
| 0.6205 | 2.9412 | 25 | 0.5954 |
| 0.4973 | 4.0 | 34 | 0.5606 |
| 0.4478 | 4.9412 | 42 | 0.5403 |
| 0.3946 | 6.0 | 51 | 0.5509 |
| 0.3109 | 6.9412 | 59 | 0.5958 |
| 0.182 | 8.0 | 68 | 0.6716 |
| 0.0682 | 8.9412 | 76 | 0.7787 |
| 0.0461 | 10.0 | 85 | 0.9119 |
| 0.03 | 10.9412 | 93 | 0.9896 |
| 0.0116 | 12.0 | 102 | 1.0825 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |