wav2vec2-large-xlsr-53-gender-recognition-librispeech
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on Librispeech-clean-100 for gender recognition. It achieves the following results on the evaluation set: - Loss: 0.0061 - F1: 0.9993
Params
320 M
Context
—
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daily snapshots · 106 days
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 1.3 GB | 1.9 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- Wav2Vec2ForSequenceClassification
- Parameters
- 320 M
- Tensor type
- F32
- Vocabulary
- 32
- Layers / heads
- 24 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2023-04-24
- Training datasets
- librispeech_asr
- Added to our catalog
- 2026-07-28
Compare with any audio-classification model