metadata

license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - wer
model-index:
  - name: tachiwin_totonac
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: ljcamargo--totonac_alpha_1
          split: test
          args: ljcamargo--totonac_alpha_1
        metrics:
          - name: Wer
            type: wer
            value: 0.6465189873417722

tachiwin_totonac

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

Loss: 1.7535
Wer: 0.6465

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: 90

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.1063	5.19	200	2.9834	1.0
2.9016	10.39	400	2.4405	0.9959
1.7606	15.58	600	1.1942	0.8532
1.0549	20.78	800	1.1132	0.7788
0.7553	25.97	1000	1.1224	0.6899
0.6639	31.51	1200	1.2641	0.7082
0.5344	36.7	1400	1.3247	0.6835
0.4527	41.9	1600	1.3915	0.7022
0.3839	47.09	1800	1.4051	0.6791
0.3065	52.29	2000	1.3899	0.6706
0.2714	57.48	2200	1.5455	0.6573
0.2437	62.68	2400	1.6798	0.6601
0.2103	67.87	2600	1.7406	0.6674
0.1899	73.06	2800	1.7625	0.6522
0.1841	78.26	3000	1.7443	0.6535
0.1544	83.45	3200	1.7405	0.6465
0.1461	88.65	3400	1.7535	0.6465

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3