

**pythia-1.4B-finetuned-oa-instructions**

This model is a fine-tuned version of pythia on the oa dataset. It achieves the following results on the evaluation set:

    Loss: 0.1224

**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:


* seed: 42
* learning_rate: 5e-06
* train_batch_size: 32
* eval_batch_size: 8
* optimizer: Adam with betas : {'lr': 5e-06, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
* lr_scheduler_type: linear
* training_steps: 5000
* fp16
* warmup_steps 5

* Num examples = 53k

**Training results**


```
{
    "epoch": 1.0,
    "train_loss": 0.8031303182039198,
    "train_runtime": 6338.6403,
    "train_samples": 53455,
    "train_samples_per_second": 8.433,
    "train_steps_per_second": 0.264
}
```



**Framework versions**

* transformers 4.24.0
* torch 1.10.0+cu111
* datasets 2.10.0
* tokenizers 0.12.1
{"license": "cc-by-4.0"}
transformers pytorch gpt_neox text-generation license:cc-by-4.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #gpt_neox #text-generation #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 



pythia-1.4B-finetuned-oa-instructions

This model is a fine-tuned version of pythia on the oa dataset. It achieves the following results on the evaluation set:

    Loss: 0.1224

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:


* seed: 42
* learning_rate: 5e-06
* train_batch_size: 32
* eval_batch_size: 8
* optimizer: Adam with betas : {'lr': 5e-06, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}
* lr_scheduler_type: linear
* training_steps: 5000
* fp16
* warmup_steps 5

* Num examples = 53k

Training results






Framework versions

* transformers 4.24.0
* torch 1.10.0+cu111
* datasets 2.10.0
* tokenizers 0.12.1
TAGS
#transformers #pytorch #gpt_neox #text-generation #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

TAGS
#transformers #pytorch #gpt_neox #text-generation #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
