openslr/librispeech_asr
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How to use speech-seq2seq/wav2vec2-2-gpt2-medium-no-adapter-frozen-enc with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="speech-seq2seq/wav2vec2-2-gpt2-medium-no-adapter-frozen-enc") # Load model directly
from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq
tokenizer = AutoTokenizer.from_pretrained("speech-seq2seq/wav2vec2-2-gpt2-medium-no-adapter-frozen-enc")
model = AutoModelForSpeechSeq2Seq.from_pretrained("speech-seq2seq/wav2vec2-2-gpt2-medium-no-adapter-frozen-enc")YAML Metadata Error:"model-index[0].name" is not allowed to be empty
This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.9364 | 0.28 | 500 | 6.3613 | 1.9833 |
| 1.941 | 0.56 | 1000 | 5.6974 | 1.9746 |
| 2.3312 | 0.84 | 1500 | 5.6979 | 1.7345 |
| 2.8004 | 1.12 | 2000 | 6.0436 | 1.6787 |
| 3.0003 | 1.4 | 2500 | 6.0955 | 1.7625 |
| 2.9677 | 1.68 | 3000 | 6.2841 | 1.6731 |
| 2.2759 | 1.96 | 3500 | 6.3094 | 1.7494 |
| 2.2989 | 2.24 | 4000 | 6.9891 | 1.9115 |
| 1.8814 | 2.52 | 4500 | 6.9818 | 1.9832 |
| 2.658 | 2.8 | 5000 | 6.5541 | 1.9877 |