metadata
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- hf-internal-testing/librispeech_asr_dummy
model-index:
- name: wft-test-model
results: []
wft-test-model
This model is a fine-tuned version of openai/whisper-tiny on the hf-internal-testing/librispeech_asr_dummy dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.6337
- eval_wer: 40.9449
- eval_cer: 73.7926
- eval_decode_time: 0.5137
- eval_wer_time: 0.0217
- eval_cer_time: 0.0030
- eval_runtime: 1.3876
- eval_samples_per_second: 7.207
- eval_steps_per_second: 1.441
- epoch: 2.02
- step: 40
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: 0.0005
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 100
Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1