README.md

metadata

license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
datasets:
  - minds14
metrics:
  - wer
model-index:
  - name: my_awesome_asr_mind_model
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: minds14
          type: minds14
          config: en-US
          split: None
          args: en-US
        metrics:
          - name: Wer
            type: wer
            value: 0.7633333333333333

my_awesome_asr_mind_model

This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 3.0211
• Wer: 0.7633

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: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1841	100.0	1000	2.4919	0.74
0.0295	200.0	2000	3.0211	0.7633

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.1
• Datasets 2.20.0
• Tokenizers 0.19.1