openslr/librispeech_asr
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How to use speech-seq2seq/wav2vec2-2-bert-large-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-bert-large-no-adapter-frozen-enc") # Load model directly
from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq
tokenizer = AutoTokenizer.from_pretrained("speech-seq2seq/wav2vec2-2-bert-large-no-adapter-frozen-enc")
model = AutoModelForSpeechSeq2Seq.from_pretrained("speech-seq2seq/wav2vec2-2-bert-large-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 |
|---|---|---|---|---|
| 5.171 | 0.28 | 500 | 8.6956 | 2.0055 |
| 5.307 | 0.56 | 1000 | 8.5958 | 2.0096 |
| 5.1449 | 0.84 | 1500 | 10.4208 | 2.0115 |
| 6.1351 | 1.12 | 2000 | 10.2950 | 2.0059 |
| 6.2997 | 1.4 | 2500 | 10.6762 | 2.0115 |
| 6.1394 | 1.68 | 3000 | 10.9190 | 2.0110 |
| 6.1868 | 1.96 | 3500 | 11.0166 | 2.0112 |
| 5.9647 | 2.24 | 4000 | 11.4154 | 2.0141 |
| 6.2202 | 2.52 | 4500 | 11.5837 | 2.0152 |
| 5.9612 | 2.8 | 5000 | 11.7664 | 2.0133 |