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# large-model-finetuned-code-alpaca

This model is a fine-tuned version of [bigcode/large-model](https://huggingface.co/bigcode/large-model) on the lewtun/code_alpaca dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1605

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1672        | 0.03  | 1    | 1.1605          |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "datasets": ["lewtun/code_alpaca"], "model-index": [{"name": "large-model-finetuned-code-alpaca", "results": []}]}
transformers pytorch tensorboard gpt_bigcode text-generation generated_from_trainer dataset:lewtun/code_alpaca autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt_bigcode #text-generation #generated_from_trainer #dataset-lewtun/code_alpaca #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

large-model-finetuned-code-alpaca
=================================


This model is a fine-tuned version of bigcode/large-model on the lewtun/code\_alpaca dataset.
It achieves the following results on the evaluation set:


* Loss: 1.1605


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: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* training\_steps: 1


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* training\_steps: 1 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt_bigcode #text-generation #generated_from_trainer #dataset-lewtun/code_alpaca #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* training\_steps: 1 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #gpt_bigcode #text-generation #generated_from_trainer #dataset-lewtun/code_alpaca #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* training\_steps: 1### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.1+cu117
* Datasets 2.10.1
* Tokenizers 0.13.3