Instructions to use harshit345/xlsr-wav2vec-speech-emotion-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harshit345/xlsr-wav2vec-speech-emotion-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="harshit345/xlsr-wav2vec-speech-emotion-recognition")# Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("harshit345/xlsr-wav2vec-speech-emotion-recognition") model = Wav2Vec2ForSpeechClassification.from_pretrained("harshit345/xlsr-wav2vec-speech-emotion-recognition") - Notebooks
- Google Colab
- Kaggle
Commit ·
7104d50
1
Parent(s): 8fcd357
Upload eval_results.json
Browse files- eval_results.json +9 -0
eval_results.json
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{
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"epoch": 4.99,
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"eval_accuracy": 0.9008264541625977,
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"eval_loss": 0.3769935369491577,
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"eval_runtime": 72.4575,
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"eval_samples": 121,
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"eval_samples_per_second": 1.67,
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"eval_steps_per_second": 0.428
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}
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