metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - xtreme_s
metrics:
  - wer
base_model: facebook/wav2vec2-base
model-index:
  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod2
    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: 1
            name: Wer

wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod2

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

Loss: 2.8837
Wer: 1.0

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: 0.005
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.962	3.08	100	2.8983	1.0
2.9085	6.15	200	2.8864	1.0
2.9094	9.23	300	2.9040	1.0
2.8976	12.31	400	2.9628	1.0
2.901	15.38	500	2.8694	1.0
2.8913	18.46	600	2.8954	1.0
2.8918	21.54	700	2.8726	1.0
2.892	24.62	800	2.8865	1.0
2.8856	27.69	900	2.9127	1.0
2.8893	30.77	1000	2.8989	1.0
2.8862	33.85	1100	2.8831	1.0
2.8853	36.92	1200	2.8960	1.0
2.8856	40.0	1300	2.8911	1.0
2.8849	43.08	1400	2.8926	1.0
2.8829	46.15	1500	2.8837	1.0
2.8812	49.23	1600	2.8859	1.0
2.8825	52.31	1700	2.8858	1.0
2.8833	55.38	1800	2.8856	1.0
2.88	58.46	1900	2.8837	1.0

Framework versions

Transformers 4.35.2
Pytorch 2.1.2+cu121
Datasets 1.18.3
Tokenizers 0.15.1