
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-large-xls-r-300m-pashto-colab-test-6

This model is a fine-tuned version of [rsd16/wav2vec2-large-xlsr-53-fine-tuned-farsi](https://huggingface.co/rsd16/wav2vec2-large-xlsr-53-fine-tuned-farsi) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0

## 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: 0.9
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss    | Epoch | Step | Validation Loss | Wer |
|:----------------:|:-----:|:----:|:---------------:|:---:|
| 1860014104903.68 | 0.96  | 100  | nan             | 1.0 |
| 0.0              | 1.91  | 200  | nan             | 1.0 |
| 0.0              | 2.87  | 300  | nan             | 1.0 |
| 0.0              | 3.82  | 400  | nan             | 1.0 |
| 0.0              | 4.78  | 500  | nan             | 1.0 |
| 0.0              | 5.73  | 600  | nan             | 1.0 |
| 0.0              | 6.69  | 700  | nan             | 1.0 |
| 0.0              | 7.64  | 800  | nan             | 1.0 |
| 0.0              | 8.6   | 900  | nan             | 1.0 |
| 0.0              | 9.55  | 1000 | nan             | 1.0 |
| 0.0              | 10.51 | 1100 | nan             | 1.0 |
| 0.0              | 11.46 | 1200 | nan             | 1.0 |
| 0.0              | 12.42 | 1300 | nan             | 1.0 |
| 0.0              | 13.37 | 1400 | nan             | 1.0 |
| 0.0              | 14.33 | 1500 | nan             | 1.0 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "datasets": ["audiofolder"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-large-xls-r-300m-pashto-colab-test-6", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "audiofolder", "type": "audiofolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "wer", "value": 1.0, "name": "Wer"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:audiofolder model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-audiofolder #model-index #endpoints_compatible #region-us 

wav2vec2-large-xls-r-300m-pashto-colab-test-6
=============================================


This model is a fine-tuned version of rsd16/wav2vec2-large-xlsr-53-fine-tuned-farsi on the audiofolder dataset.
It achieves the following results on the evaluation set:


* Loss: nan
* Wer: 1.0


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: 0.9
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 10
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 15
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.9
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 10
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #generated_from_trainer #dataset-audiofolder #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.9
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 10
* total\_train\_batch\_size: 10
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 10
* num\_epochs: 15
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3