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# 

This model was trained from scratch on the xtreme_s dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1356
- Bleu: 0.0000

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.6458        | 0.31  | 500  | 4.3754          | 0.0    |
| 2.3505        | 0.62  | 1000 | 4.3071          | 0.0    |
| 2.2152        | 0.93  | 1500 | 3.9444          | 0.0    |
| 2.79          | 1.23  | 2000 | 3.2046          | 0.0000 |
| 2.569         | 1.54  | 2500 | 2.6812          | 0.0000 |
| 2.322         | 1.85  | 3000 | 2.4081          | 0.0000 |
| 2.3435        | 2.16  | 3500 | 2.2696          | 0.0000 |
| 2.2063        | 2.47  | 4000 | 2.2452          | 0.0000 |
| 2.1087        | 2.78  | 4500 | 2.1356          | 0.0000 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 2.1.1.dev0
- Tokenizers 0.11.0

{"tags": ["generated_from_trainer"], "datasets": ["xtreme_s"], "metrics": ["bleu"], "model-index": [{"name": "", "results": []}]}
transformers pytorch tensorboard speech-encoder-decoder automatic-speech-recognition generated_from_trainer dataset:xtreme_s endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-xtreme_s #endpoints_compatible #region-us 


This model was trained from scratch on the xtreme\_s dataset.
It achieves the following results on the evaluation set:


* Loss: 2.1356
* Bleu: 0.0000


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: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 3.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 2.1.1.dev0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 3.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 2.1.1.dev0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-xtreme_s #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 3.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 2.1.1.dev0
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #speech-encoder-decoder #automatic-speech-recognition #generated_from_trainer #dataset-xtreme_s #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 3.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.19.0.dev0
* Pytorch 1.10.2+cu113
* Datasets 2.1.1.dev0
* Tokenizers 0.11.0