transformers safetensors llama text-generation generated_from_trainer base_model:deepseek-ai/deepseek-coder-6.7b-instruct license:other autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: other
base_model: deepseek-ai/deepseek-coder-6.7b-instruct
tags:
- generated_from_trainer
model-index:
- name: finetune_deepspeed_deepseek
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetune_deepspeed_deepseek

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2286

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1482        | 1.0   | 1559  | 0.2420          |
| 0.0969        | 2.0   | 3118  | 0.2178          |
| 0.0761        | 3.0   | 4677  | 0.1981          |
| 0.0561        | 4.0   | 6236  | 0.1966          |
| 0.0469        | 5.0   | 7795  | 0.1977          |
| 0.0401        | 6.0   | 9354  | 0.1979          |
| 0.032         | 7.0   | 10913 | 0.2009          |
| 0.028         | 8.0   | 12472 | 0.2091          |
| 0.0254        | 9.0   | 14031 | 0.2252          |
| 0.0275        | 10.0  | 15590 | 0.2286          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
