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# wav2vec2-xlsr-ft-cy-btb

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3938
- Wer: 0.9983

## 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: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.33  | 100  | 3.7176          | 1.0    |
| No log        | 0.66  | 200  | 3.0649          | 1.0    |
| No log        | 1.0   | 300  | 2.9714          | 1.0    |
| No log        | 1.33  | 400  | 1.3840          | 0.8891 |
| 3.628         | 1.66  | 500  | 1.0746          | 0.7500 |
| 3.628         | 1.99  | 600  | 0.8992          | 0.6832 |
| 3.628         | 2.33  | 700  | 0.8292          | 0.6175 |
| 3.628         | 2.66  | 800  | 0.8293          | 0.6080 |
| 3.628         | 2.99  | 900  | 0.6632          | 0.5244 |
| 0.8635        | 3.32  | 1000 | 0.6550          | 0.4947 |
| 0.8635        | 3.65  | 1100 | 0.6255          | 0.4777 |
| 0.8635        | 3.99  | 1200 | 0.5891          | 0.4465 |
| 0.8635        | 4.32  | 1300 | 0.7092          | 0.5183 |
| 0.8635        | 4.65  | 1400 | 1.0072          | 0.6188 |
| 0.8316        | 4.98  | 1500 | 1.2552          | 0.9375 |
| 0.8316        | 5.32  | 1600 | 1.4598          | 0.8563 |
| 0.8316        | 5.65  | 1700 | 1.6682          | 0.8975 |
| 0.8316        | 5.98  | 1800 | 1.8454          | 0.9660 |
| 0.8316        | 6.31  | 1900 | 2.0722          | 0.9919 |
| 1.8552        | 6.64  | 2000 | 2.0574          | 0.9931 |
| 1.8552        | 6.98  | 2100 | 2.1060          | 0.9887 |
| 1.8552        | 7.31  | 2200 | 2.0413          | 0.9771 |
| 1.8552        | 7.64  | 2300 | 1.9971          | 0.9765 |
| 1.8552        | 7.97  | 2400 | 1.9847          | 0.9742 |
| 2.1436        | 8.31  | 2500 | 2.0486          | 0.9700 |
| 2.1436        | 8.64  | 2600 | 2.1406          | 0.9661 |
| 2.1436        | 8.97  | 2700 | 2.3666          | 0.9527 |
| 2.1436        | 9.3   | 2800 | 2.2622          | 0.9692 |
| 2.1436        | 9.63  | 2900 | 2.2790          | 0.9943 |
| 2.3335        | 9.97  | 3000 | 2.3607          | 0.9972 |
| 2.3335        | 10.3  | 3100 | 2.3924          | 0.9983 |
| 2.3335        | 10.63 | 3200 | 2.3938          | 0.9983 |
| 2.3335        | 10.96 | 3300 | 2.3938          | 0.9983 |
| 2.3335        | 11.3  | 3400 | 2.3938          | 0.9983 |
| 2.4814        | 11.63 | 3500 | 2.3938          | 0.9983 |
| 2.4814        | 11.96 | 3600 | 2.3938          | 0.9983 |
| 2.4814        | 12.29 | 3700 | 2.3938          | 0.9983 |
| 2.4814        | 12.62 | 3800 | 2.3938          | 0.9983 |
| 2.4814        | 12.96 | 3900 | 2.3938          | 0.9983 |
| 2.4882        | 13.29 | 4000 | 2.3938          | 0.9983 |
| 2.4882        | 13.62 | 4100 | 2.3938          | 0.9983 |
| 2.4882        | 13.95 | 4200 | 2.3938          | 0.9983 |
| 2.4882        | 14.29 | 4300 | 2.3938          | 0.9983 |
| 2.4882        | 14.62 | 4400 | 2.3938          | 0.9983 |
| 2.4818        | 14.95 | 4500 | 2.3938          | 0.9983 |
| 2.4818        | 15.28 | 4600 | 2.3938          | 0.9983 |
| 2.4818        | 15.61 | 4700 | 2.3938          | 0.9983 |
| 2.4818        | 15.95 | 4800 | 2.3938          | 0.9983 |
| 2.4818        | 16.28 | 4900 | 2.3938          | 0.9983 |
| 2.487         | 16.61 | 5000 | 2.3938          | 0.9983 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- 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-cy-btb", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - CY", "type": "banc-trawsgrifiadau-bangor", "config": "cy", "split": "test", "args": "Config: cy, Training split: train, Eval split: test"}, "metrics": [{"type": "wer", "value": 0.9982730767088185, "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-cy-btb
=======================


This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - CY dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3938
* Wer: 0.9983


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: 32
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0003
* train\_batch\_size: 32
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* 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: 32
* eval\_batch\_size: 128
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 800
* training\_steps: 5000
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3