transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_11_0 base_model:facebook/wav2vec2-large-xlsr-53 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-sw
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: sw
      split: test
      args: sw
    metrics:
    - name: Wer
      type: wer
      value: 0.3230712635221355
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xlsr-sw

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4334
- Wer: 0.3231

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.3405        | 0.88  | 400   | 2.8882          | 1.0000 |
| 1.083         | 1.77  | 800   | 0.5223          | 0.5849 |
| 0.4721        | 2.65  | 1200  | 0.3921          | 0.4667 |
| 0.3793        | 3.54  | 1600  | 0.3725          | 0.4257 |
| 0.3264        | 4.42  | 2000  | 0.3646          | 0.4179 |
| 0.294         | 5.31  | 2400  | 0.3542          | 0.4104 |
| 0.2623        | 6.19  | 2800  | 0.3576          | 0.3892 |
| 0.2408        | 7.08  | 3200  | 0.3516          | 0.3876 |
| 0.2229        | 7.96  | 3600  | 0.3580          | 0.3877 |
| 0.206         | 8.85  | 4000  | 0.3466          | 0.3683 |
| 0.1991        | 9.73  | 4400  | 0.3306          | 0.3783 |
| 0.1863        | 10.62 | 4800  | 0.3605          | 0.3707 |
| 0.1743        | 11.5  | 5200  | 0.3483          | 0.3703 |
| 0.1678        | 12.39 | 5600  | 0.3645          | 0.3618 |
| 0.1547        | 13.27 | 6000  | 0.3671          | 0.3589 |
| 0.152         | 14.16 | 6400  | 0.3733          | 0.3568 |
| 0.144         | 15.04 | 6800  | 0.3684          | 0.3486 |
| 0.136         | 15.93 | 7200  | 0.3558          | 0.3493 |
| 0.1262        | 16.81 | 7600  | 0.3748          | 0.3486 |
| 0.1222        | 17.7  | 8000  | 0.3774          | 0.3466 |
| 0.1164        | 18.58 | 8400  | 0.3840          | 0.3427 |
| 0.1108        | 19.47 | 8800  | 0.3988          | 0.3438 |
| 0.1072        | 20.35 | 9200  | 0.4020          | 0.3384 |
| 0.1008        | 21.24 | 9600  | 0.4013          | 0.3375 |
| 0.0982        | 22.12 | 10000 | 0.4162          | 0.3361 |
| 0.0951        | 23.01 | 10400 | 0.4107          | 0.3346 |
| 0.0923        | 23.89 | 10800 | 0.4248          | 0.3337 |
| 0.0866        | 24.78 | 11200 | 0.4151          | 0.3295 |
| 0.0875        | 25.66 | 11600 | 0.4211          | 0.3310 |
| 0.0813        | 26.55 | 12000 | 0.4303          | 0.3290 |
| 0.0775        | 27.43 | 12400 | 0.4334          | 0.3249 |
| 0.0759        | 28.32 | 12800 | 0.4312          | 0.3240 |
| 0.0758        | 29.2  | 13200 | 0.4334          | 0.3231 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
