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# layer_9,10,11,12,13

This model is a fine-tuned version of [EleutherAI/pythia-1b-deduped](https://huggingface.co/EleutherAI/pythia-1b-deduped) on the eli5 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4496
- Accuracy: 0.4952

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3186        | 5.93  | 200  | 4.3850          | 0.1399   |
| 2.7653        | 11.85 | 400  | 2.7820          | 0.4294   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.1+rocm5.4.2
- Datasets 2.11.0
- Tokenizers 0.13.3


## Wandb Report
 https://wandb.ai/ontocord/jason-test-pythia-1b-deduped-layer-test-eli5/runs/eecbe79c
{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["eli5"], "metrics": ["accuracy"], "model-index": [{"name": "layer_9,10,11,12,13", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "eli5", "type": "eli5", "split": "None"}, "metrics": [{"type": "accuracy", "value": 0.49515362035225047, "name": "Accuracy"}]}]}]}
transformers pytorch gpt_neox text-generation generated_from_trainer dataset:eli5 license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt_neox #text-generation #generated_from_trainer #dataset-eli5 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

layer\_9,10,11,12,13
====================


This model is a fine-tuned version of EleutherAI/pythia-1b-deduped on the eli5 dataset.
It achieves the following results on the evaluation set:


* Loss: 2.4496
* Accuracy: 0.4952


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: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+rocm5.4.2
* Datasets 2.11.0
* Tokenizers 0.13.3


Wandb Report
------------


URL



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+rocm5.4.2
* Datasets 2.11.0
* Tokenizers 0.13.3


Wandb Report
------------


URL
TAGS
#transformers #pytorch #gpt_neox #text-generation #generated_from_trainer #dataset-eli5 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 8
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.1+rocm5.4.2
* Datasets 2.11.0
* Tokenizers 0.13.3


Wandb Report
------------


URL