End of training

README.md

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+---
+license: apache-2.0
+tags:
+- Speech Emotion Recognition
+- generated_from_trainer
+datasets:
+- dusha_emotion_audio
+metrics:
+- accuracy
+model-index:
+- name: Wav2vec2-xls-r-300m
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Wav2vec2-xls-r-300m
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the KELONMYOSA/dusha_emotion_audio dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5633
+- Accuracy: 0.7970
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.003
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.7868        | 1.0   | 24170  | 0.7561          | 0.7318   |
+| 0.7147        | 2.0   | 48340  | 0.6984          | 0.7459   |
+| 0.669         | 3.0   | 72510  | 0.6263          | 0.7727   |
+| 0.6362        | 4.0   | 96680  | 0.5832          | 0.7902   |
+| 0.4476        | 5.0   | 120850 | 0.5633          | 0.7970   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3