Supreeta03
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Supreeta03/wav2vec-base-CREMA-sentiment-analysis-best1
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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: wav2vec-base-CREMA-sentiment-analysis
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# wav2vec-base-CREMA-sentiment-analysis
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3834
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- Accuracy: 0.5756
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.7533 | 0.99 | 37 | 1.7438 | 0.3056 |
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| 1.5942 | 1.99 | 74 | 1.5781 | 0.3409 |
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| 1.4434 | 2.98 | 111 | 1.5167 | 0.3568 |
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| 1.4327 | 4.0 | 149 | 1.4241 | 0.4156 |
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| 1.3499 | 4.99 | 186 | 1.3148 | 0.4819 |
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| 1.2126 | 5.99 | 223 | 1.2915 | 0.4887 |
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| 1.1838 | 6.98 | 260 | 1.2672 | 0.4971 |
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| 1.1141 | 8.0 | 298 | 1.2433 | 0.5046 |
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| 1.1163 | 8.99 | 335 | 1.1968 | 0.5281 |
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| 1.0099 | 9.99 | 372 | 1.1610 | 0.5516 |
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| 0.9566 | 10.98 | 409 | 1.1547 | 0.5567 |
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| 0.906 | 12.0 | 447 | 1.1565 | 0.5584 |
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| 0.8275 | 12.99 | 484 | 1.1442 | 0.5718 |
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| 0.7813 | 13.99 | 521 | 1.2570 | 0.5550 |
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| 0.711 | 14.98 | 558 | 1.1654 | 0.5567 |
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| 0.7146 | 16.0 | 596 | 1.4391 | 0.5323 |
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| 0.6597 | 16.99 | 633 | 1.2309 | 0.5659 |
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| 0.5579 | 17.99 | 670 | 1.2385 | 0.5760 |
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| 0.5874 | 18.98 | 707 | 1.2609 | 0.5760 |
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| 0.4905 | 20.0 | 745 | 1.3433 | 0.5777 |
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| 0.5089 | 20.99 | 782 | 1.3727 | 0.5584 |
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| 0.4414 | 21.99 | 819 | 1.3488 | 0.5676 |
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| 0.3837 | 22.98 | 856 | 1.3572 | 0.5819 |
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| 0.4419 | 24.0 | 894 | 1.5063 | 0.5651 |
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| 0.387 | 24.99 | 931 | 1.4656 | 0.5659 |
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| 0.4068 | 25.99 | 968 | 1.5354 | 0.5701 |
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| 0.3496 | 26.98 | 1005 | 1.4607 | 0.5684 |
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| 0.3579 | 28.0 | 1043 | 1.5049 | 0.5651 |
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| 0.3135 | 28.99 | 1080 | 1.4441 | 0.5743 |
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| 0.3612 | 29.99 | 1117 | 1.5329 | 0.5701 |
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| 0.2599 | 30.98 | 1154 | 1.5920 | 0.5668 |
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| 0.2517 | 32.0 | 1192 | 1.5633 | 0.5626 |
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| 0.2439 | 32.99 | 1229 | 1.5979 | 0.5718 |
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| 0.2891 | 33.99 | 1266 | 1.5590 | 0.5785 |
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| 0.2564 | 34.98 | 1303 | 1.5978 | 0.5751 |
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| 0.2132 | 36.0 | 1341 | 1.6400 | 0.5634 |
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| 0.1882 | 36.99 | 1378 | 1.6309 | 0.5718 |
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| 0.2027 | 37.99 | 1415 | 1.6376 | 0.5743 |
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| 0.2555 | 38.98 | 1452 | 1.7064 | 0.5693 |
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| 0.1872 | 40.0 | 1490 | 1.6575 | 0.5819 |
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| 0.1891 | 40.99 | 1527 | 1.6606 | 0.5735 |
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| 0.1795 | 41.99 | 1564 | 1.6507 | 0.5735 |
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| 0.1931 | 42.98 | 1601 | 1.6627 | 0.5760 |
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| 0.1574 | 44.0 | 1639 | 1.6944 | 0.5802 |
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| 0.1842 | 44.99 | 1676 | 1.7082 | 0.5768 |
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| 0.1859 | 45.99 | 1713 | 1.7004 | 0.5768 |
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| 0.2088 | 46.98 | 1750 | 1.7002 | 0.5802 |
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| 0.197 | 48.0 | 1788 | 1.6969 | 0.5751 |
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| 0.1902 | 48.99 | 1825 | 1.6996 | 0.5743 |
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| 0.1771 | 49.66 | 1850 | 1.6998 | 0.5743 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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