---
license: apache-2.0
base_model: mosaicml/mpt-7b-instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: mpt_1000_STEPS_1e5_SFT_SFT
  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. -->

# mpt_1000_STEPS_1e5_SFT_SFT

This model is a fine-tuned version of [mosaicml/mpt-7b-instruct](https://huggingface.co/mosaicml/mpt-7b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3857

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5003        | 0.05  | 50   | 0.4827          |
| 0.4582        | 0.1   | 100  | 0.5370          |
| 0.485         | 0.15  | 150  | 0.4682          |
| 0.5202        | 0.2   | 200  | 0.4486          |
| 0.4687        | 0.24  | 250  | 0.4494          |
| 0.469         | 0.29  | 300  | 0.4485          |
| 0.4331        | 0.34  | 350  | 0.4359          |
| 0.4189        | 0.39  | 400  | 0.4268          |
| 0.4444        | 0.44  | 450  | 0.4190          |
| 0.4187        | 0.49  | 500  | 0.4140          |
| 0.4045        | 0.54  | 550  | 0.4090          |
| 0.4159        | 0.59  | 600  | 0.4021          |
| 0.3862        | 0.64  | 650  | 0.3973          |
| 0.3773        | 0.68  | 700  | 0.3930          |
| 0.382         | 0.73  | 750  | 0.3893          |
| 0.3892        | 0.78  | 800  | 0.3873          |
| 0.4079        | 0.83  | 850  | 0.3862          |
| 0.3667        | 0.88  | 900  | 0.3857          |
| 0.3724        | 0.93  | 950  | 0.3857          |
| 0.3908        | 0.98  | 1000 | 0.3857          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2