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wav2vec2-base-finetuned-ks

Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Inference Endpoints
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update model card README.md

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  1. README.md +13 -13
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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.7989778796620587
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2427
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- - F1: 0.7990
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 2.288 | 1.0 | 688 | 2.1254 | 0.3776 |
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- | 1.2835 | 2.0 | 1376 | 1.5632 | 0.5701 |
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- | 1.185 | 3.0 | 2064 | 1.4202 | 0.6411 |
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- | 0.698 | 4.0 | 2752 | 1.1339 | 0.7376 |
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- | 0.8794 | 5.0 | 3440 | 1.1006 | 0.7657 |
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- | 0.2322 | 6.0 | 4128 | 1.1390 | 0.7883 |
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- | 0.3386 | 7.0 | 4816 | 1.2427 | 0.7990 |
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- | 0.0077 | 8.0 | 5504 | 1.3179 | 0.7820 |
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- | 0.1609 | 9.0 | 6192 | 1.3100 | 0.7940 |
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- | 0.0049 | 10.0 | 6880 | 1.2323 | 0.7948 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.8016517743184772
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1858
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+ - F1: 0.8017
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 2.6077 | 1.0 | 602 | 2.5802 | 0.1587 |
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+ | 1.9999 | 2.0 | 1204 | 2.0069 | 0.3600 |
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+ | 1.4107 | 3.0 | 1806 | 1.6226 | 0.5527 |
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+ | 0.9977 | 4.0 | 2408 | 1.2932 | 0.6719 |
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+ | 0.8132 | 5.0 | 3010 | 1.2297 | 0.7030 |
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+ | 0.5315 | 6.0 | 3612 | 1.0131 | 0.7745 |
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+ | 0.5772 | 7.0 | 4214 | 1.1444 | 0.7782 |
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+ | 0.0248 | 8.0 | 4816 | 1.1777 | 0.7850 |
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+ | 0.0186 | 9.0 | 5418 | 1.2235 | 0.7910 |
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+ | 0.2457 | 10.0 | 6020 | 1.1858 | 0.8017 |
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  ### Framework versions