
<!-- 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-xlsr-ft-btb

This model is a fine-tuned version of [techiaith/wav2vec2-xlsr-ft-cy](https://huggingface.co/techiaith/wav2vec2-xlsr-ft-cy) on the TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3862
- Wer: 0.2817

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.21  | 100  | 3.1084          | 1.0    |
| No log        | 0.41  | 200  | 1.4742          | 0.7157 |
| No log        | 0.62  | 300  | 0.7243          | 0.4482 |
| No log        | 0.83  | 400  | 0.5905          | 0.4043 |
| 2.399         | 1.03  | 500  | 0.5406          | 0.3665 |
| 2.399         | 1.24  | 600  | 0.5380          | 0.3699 |
| 2.399         | 1.44  | 700  | 0.4905          | 0.3580 |
| 2.399         | 1.65  | 800  | 0.5045          | 0.3727 |
| 2.399         | 1.86  | 900  | 0.4783          | 0.3474 |
| 0.6123        | 2.06  | 1000 | 0.4372          | 0.3272 |
| 0.6123        | 2.27  | 1100 | 0.4305          | 0.3225 |
| 0.6123        | 2.48  | 1200 | 0.4292          | 0.3141 |
| 0.6123        | 2.68  | 1300 | 0.4136          | 0.3233 |
| 0.6123        | 2.89  | 1400 | 0.4053          | 0.3140 |
| 0.4645        | 3.1   | 1500 | 0.4207          | 0.3261 |
| 0.4645        | 3.3   | 1600 | 0.4133          | 0.3130 |
| 0.4645        | 3.51  | 1700 | 0.4283          | 0.3118 |
| 0.4645        | 3.72  | 1800 | 0.4030          | 0.2982 |
| 0.4645        | 3.92  | 1900 | 0.3833          | 0.2911 |
| 0.3708        | 4.13  | 2000 | 0.3933          | 0.2966 |
| 0.3708        | 4.33  | 2100 | 0.3947          | 0.2902 |
| 0.3708        | 4.54  | 2200 | 0.3878          | 0.2849 |
| 0.3708        | 4.75  | 2300 | 0.3915          | 0.2854 |
| 0.3708        | 4.95  | 2400 | 0.3865          | 0.2811 |


### Framework versions

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

{"license": "apache-2.0", "tags": ["automatic-speech-recognition", "techiaith/banc-trawsgrifiadau-bangor", "generated_from_trainer"], "datasets": ["banc-trawsgrifiadau-bangor"], "metrics": ["wer"], "model-index": [{"name": "wav2vec2-xlsr-ft-btb", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - NA", "type": "banc-trawsgrifiadau-bangor", "config": "default", "split": "test", "args": "Config: na, Training split: train, Eval split: test"}, "metrics": [{"type": "wer", "value": 0.28168787244322757, "name": "Wer"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition techiaith/banc-trawsgrifiadau-bangor generated_from_trainer dataset:banc-trawsgrifiadau-bangor license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #techiaith/banc-trawsgrifiadau-bangor #generated_from_trainer #dataset-banc-trawsgrifiadau-bangor #license-apache-2.0 #model-index #endpoints_compatible #region-us 

wav2vec2-xlsr-ft-btb
====================


This model is a fine-tuned version of techiaith/wav2vec2-xlsr-ft-cy on the TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - NA dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3862
* Wer: 0.2817


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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 5.0
* mixed\_precision\_training: Native AMP


### 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: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 5.0
* mixed\_precision\_training: Native AMP ### 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 #wav2vec2 #automatic-speech-recognition #techiaith/banc-trawsgrifiadau-bangor #generated_from_trainer #dataset-banc-trawsgrifiadau-bangor #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 5.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


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