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# bloomz-1b1-eli5-pretrained

This model is a fine-tuned version of [bigscience/bloomz-1b1](https://huggingface.co/bigscience/bloomz-1b1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1743

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2783        | 0.4   | 1000 | 3.1924          |
| 3.1211        | 0.8   | 2000 | 3.1743          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "bigscience-bloom-rail-1.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bloomz-1b1-eli5-pretrained", "results": []}]}
transformers pytorch tensorboard bloom text-generation generated_from_trainer license:bigscience-bloom-rail-1.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #bloom #text-generation #generated_from_trainer #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

bloomz-1b1-eli5-pretrained
==========================


This model is a fine-tuned version of bigscience/bloomz-1b1 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.1743


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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 2500


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 2500 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bloom #text-generation #generated_from_trainer #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 2500 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bloom #text-generation #generated_from_trainer #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 100
* training\_steps: 2500### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3