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# santacoder-finetuned-the-stack-rust

This model is a fine-tuned version of [bigcode/santacoder](https://huggingface.co/bigcode/santacoder) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7999

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.2075        | 0.05  | 500   | 1.0610          |
| 1.79          | 0.1   | 1000  | 1.0754          |
| 1.2441        | 0.15  | 1500  | 1.0339          |
| 1.1709        | 0.2   | 2000  | 0.9829          |
| 0.7645        | 0.25  | 2500  | 0.9738          |
| 1.0381        | 0.3   | 3000  | 0.9536          |
| 1.0625        | 0.35  | 3500  | 0.9268          |
| 0.78          | 0.4   | 4000  | 0.9130          |
| 0.9294        | 0.45  | 4500  | 0.9001          |
| 0.9767        | 0.5   | 5000  | 0.8857          |
| 5.7027        | 0.55  | 5500  | 0.8728          |
| 0.9476        | 0.6   | 6000  | 0.8556          |
| 0.6185        | 0.65  | 6500  | 0.8404          |
| 0.5057        | 0.7   | 7000  | 0.8328          |
| 0.6451        | 0.75  | 7500  | 0.8199          |
| 0.8298        | 0.8   | 8000  | 0.8111          |
| 0.2447        | 0.85  | 8500  | 0.8069          |
| 0.8177        | 0.9   | 9000  | 0.8020          |
| 0.7184        | 0.95  | 9500  | 0.8003          |
| 0.9166        | 1.0   | 10000 | 0.7999          |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2

{"license": "openrail", "tags": ["generated_from_trainer"], "model-index": [{"name": "santacoder-finetuned-the-stack-rust", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer custom_code license:openrail autotrain_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #custom_code #license-openrail #autotrain_compatible #text-generation-inference #region-us 

santacoder-finetuned-the-stack-rust
===================================


This model is a fine-tuned version of bigcode/santacoder on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.7999


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: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 10000


### Training results



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 10000 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #custom_code #license-openrail #autotrain_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 10000 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #custom_code #license-openrail #autotrain_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 8
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 10000### Training results### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.7.1
* Tokenizers 0.13.2