metadata

license: apache-2.0
tags:
  - generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
  - xtreme_s
metrics:
  - wer
model-index:
  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod9
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: xtreme_s
          type: xtreme_s
          config: fleurs.id_id
          split: test
          args: fleurs.id_id
        metrics:
          - type: wer
            value: 0.9842089507558749
            name: Wer

wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod9

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

Loss: 1.3012
Wer: 0.9842

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: 0.001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	39	2.8812	1.0
No log	2.0	78	2.8688	1.0
No log	3.0	117	2.8722	1.0
No log	4.0	156	2.8640	1.0
No log	5.0	195	2.8447	1.0
No log	6.0	234	2.8468	1.0
No log	7.0	273	2.8465	1.0
No log	8.0	312	2.8488	1.0
No log	9.0	351	2.8355	1.0
No log	10.0	390	2.8167	1.0
No log	11.0	429	2.8076	1.0
No log	12.0	468	2.7065	1.0
2.9881	13.0	507	2.5506	1.0
2.9881	14.0	546	2.2657	1.0
2.9881	15.0	585	1.9921	1.0
2.9881	16.0	624	1.7390	1.0
2.9881	17.0	663	1.5309	1.0
2.9881	18.0	702	1.4300	0.9994
2.9881	19.0	741	1.3280	0.9938
2.9881	20.0	780	1.3012	0.9842

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2