End of training

README.md

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+---
+license: apache-2.0
+base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-large-xlsr-53-english-finetuned-ravdess-v7
+  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-large-xlsr-53-english-finetuned-ravdess-v7
+
+This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2583
+- Accuracy: 0.6597
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9468        | 0.15  | 25   | 1.0477          | 0.5833   |
+| 0.9825        | 0.31  | 50   | 1.0943          | 0.5556   |
+| 0.83          | 0.46  | 75   | 1.0094          | 0.6389   |
+| 0.9219        | 0.62  | 100  | 1.1035          | 0.5833   |
+| 0.9044        | 0.77  | 125  | 1.2343          | 0.5833   |
+| 0.9362        | 0.93  | 150  | 1.2651          | 0.5972   |
+| 0.8799        | 1.08  | 175  | 1.2690          | 0.5486   |
+| 0.8219        | 1.23  | 200  | 1.1401          | 0.5764   |
+| 0.7739        | 1.39  | 225  | 1.2107          | 0.5417   |
+| 0.87          | 1.54  | 250  | 1.1299          | 0.6319   |
+| 0.6298        | 1.7   | 275  | 0.9628          | 0.6736   |
+| 0.5578        | 1.85  | 300  | 1.5402          | 0.5417   |
+| 0.7363        | 2.01  | 325  | 1.0680          | 0.6667   |
+| 0.5354        | 2.16  | 350  | 0.9104          | 0.6736   |
+| 0.4246        | 2.31  | 375  | 0.9475          | 0.6667   |
+| 0.479         | 2.47  | 400  | 1.2755          | 0.6597   |
+| 0.5133        | 2.62  | 425  | 0.8993          | 0.7083   |
+| 0.3661        | 2.78  | 450  | 1.0620          | 0.6667   |
+| 0.3664        | 2.93  | 475  | 1.0617          | 0.6875   |
+| 0.4177        | 3.09  | 500  | 1.2583          | 0.6597   |
+| 0.4462        | 3.24  | 525  | 0.9819          | 0.7361   |
+| 0.3419        | 3.4   | 550  | 1.2685          | 0.6667   |
+| 0.5142        | 3.55  | 575  | 0.9290          | 0.75     |
+| 0.2887        | 3.7   | 600  | 1.0275          | 0.7153   |
+| 0.2485        | 3.86  | 625  | 0.7754          | 0.7778   |
+| 0.3065        | 4.01  | 650  | 1.0046          | 0.7431   |
+| 0.1812        | 4.17  | 675  | 0.9867          | 0.7361   |
+| 0.1541        | 4.32  | 700  | 1.1906          | 0.6875   |
+| 0.2993        | 4.48  | 725  | 0.9916          | 0.75     |
+| 0.2149        | 4.63  | 750  | 1.0387          | 0.7222   |
+| 0.1114        | 4.78  | 775  | 0.9461          | 0.7292   |
+| 0.1897        | 4.94  | 800  | 0.9165          | 0.75     |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3