DunnBC22
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wav2vec2-base-Speech_Emotion_Recognition

Audio Classification

generated_from_trainer

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DunnBC22 commited on Jul 27, 2023

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@@ -19,19 +19,23 @@ pipeline_tag: audio-classification
 # wav2vec2-base-Speech_Emotion_Recognition
-This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.7264
 - Accuracy: 0.7539
-- Weighted f1: 0.7514
-- Micro f1: 0.7539
-- Macro f1: 0.7529
-- Weighted recall: 0.7539
-- Micro recall: 0.7539
-- Macro recall: 0.7577
-- Weighted precision: 0.7565
-- Micro precision: 0.7539
-- Macro precision: 0.7558
 ## Model description
@@ -65,7 +69,7 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
 | 1.5581        | 0.98  | 43   | 1.4046          | 0.4653   | 0.4080      | 0.4653   | 0.4174   | 0.4653          | 0.4653       | 0.4793       | 0.5008             | 0.4653          | 0.4974          |
 | 1.5581        | 1.98  | 86   | 1.1566          | 0.5997   | 0.5836      | 0.5997   | 0.5871   | 0.5997          | 0.5997       | 0.6093       | 0.6248             | 0.5997          | 0.6209          |

 # wav2vec2-base-Speech_Emotion_Recognition
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base).
 It achieves the following results on the evaluation set:
 - Loss: 0.7264
 - Accuracy: 0.7539
+- F1
+  - Weighted: 0.7514
+  - Micro: 0.7539
+  - Macro: 0.7529
+- Recall
+  - Weighted: 0.7539
+  - Micro: 0.7539
+  - Macro: 0.7577
+- Precision
+  - Weighted: 0.7565
+  - Micro: 0.7539
+  - Macro: 0.7558
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
 | 1.5581        | 0.98  | 43   | 1.4046          | 0.4653   | 0.4080      | 0.4653   | 0.4174   | 0.4653          | 0.4653       | 0.4793       | 0.5008             | 0.4653          | 0.4974          |
 | 1.5581        | 1.98  | 86   | 1.1566          | 0.5997   | 0.5836      | 0.5997   | 0.5871   | 0.5997          | 0.5997       | 0.6093       | 0.6248             | 0.5997          | 0.6209          |