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# wav2vec2-base-stac-local

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9746
- Wer: 0.7828
- Cer: 0.3202

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.0603        | 1.0   | 2369  | 2.1282          | 0.9517 | 0.5485 |
| 1.6155        | 2.0   | 4738  | 1.6196          | 0.9060 | 0.4565 |
| 1.3462        | 3.0   | 7107  | 1.4331          | 0.8379 | 0.3983 |
| 1.1819        | 4.0   | 9476  | 1.3872          | 0.8233 | 0.3717 |
| 1.0189        | 5.0   | 11845 | 1.4066          | 0.8328 | 0.3660 |
| 0.9026        | 6.0   | 14214 | 1.3502          | 0.8198 | 0.3508 |
| 0.777         | 7.0   | 16583 | 1.3016          | 0.7922 | 0.3433 |
| 0.7109        | 8.0   | 18952 | 1.2662          | 0.8302 | 0.3510 |
| 0.6766        | 9.0   | 21321 | 1.4321          | 0.8103 | 0.3368 |
| 0.6078        | 10.0  | 23690 | 1.3592          | 0.7871 | 0.3360 |
| 0.5958        | 11.0  | 26059 | 1.4389          | 0.7819 | 0.3397 |
| 0.5094        | 12.0  | 28428 | 1.3391          | 0.8017 | 0.3239 |
| 0.4567        | 13.0  | 30797 | 1.4718          | 0.8026 | 0.3347 |
| 0.4448        | 14.0  | 33166 | 1.7450          | 0.8043 | 0.3424 |
| 0.3976        | 15.0  | 35535 | 1.4581          | 0.7888 | 0.3283 |
| 0.3449        | 16.0  | 37904 | 1.5688          | 0.8078 | 0.3397 |
| 0.3046        | 17.0  | 40273 | 1.8630          | 0.8060 | 0.3448 |
| 0.2983        | 18.0  | 42642 | 1.8400          | 0.8190 | 0.3425 |
| 0.2728        | 19.0  | 45011 | 1.6726          | 0.8034 | 0.3280 |
| 0.2579        | 20.0  | 47380 | 1.6661          | 0.8138 | 0.3249 |
| 0.2169        | 21.0  | 49749 | 1.7389          | 0.8138 | 0.3277 |
| 0.2498        | 22.0  | 52118 | 1.7205          | 0.7948 | 0.3207 |
| 0.1831        | 23.0  | 54487 | 1.8641          | 0.8103 | 0.3229 |
| 0.1927        | 24.0  | 56856 | 1.8724          | 0.7784 | 0.3251 |
| 0.1649        | 25.0  | 59225 | 1.9187          | 0.7974 | 0.3277 |
| 0.1594        | 26.0  | 61594 | 1.9022          | 0.7828 | 0.3220 |
| 0.1338        | 27.0  | 63963 | 1.9303          | 0.7862 | 0.3212 |
| 0.1441        | 28.0  | 66332 | 1.9528          | 0.7845 | 0.3207 |
| 0.129         | 29.0  | 68701 | 1.9676          | 0.7819 | 0.3212 |
| 0.1169        | 30.0  | 71070 | 1.9746          | 0.7828 | 0.3202 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.8.1+cu102
- Datasets 1.18.3
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "wav2vec2-base-stac-local", "results": []}]}
transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

wav2vec2-base-stac-local
========================


This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9746
* Wer: 0.7828
* Cer: 0.3202


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: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu102
* Datasets 1.18.3
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu102
* Datasets 1.18.3
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu102
* Datasets 1.18.3
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* gradient\_accumulation\_steps: 2
* total\_train\_batch\_size: 2
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 30### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.8.1+cu102
* Datasets 1.18.3
* Tokenizers 0.12.1