End of training
Browse files- README.md +70 -0
- model.safetensors +1 -1
README.md
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---
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license: mit
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base_model: microsoft/deberta-v3-large
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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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- f1
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- precision
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- recall
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model-index:
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- name: deberta-v3-large-imdb
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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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# deberta-v3-large-imdb
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1906
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- Accuracy: 0.9646
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- F1: 0.9645
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- Precision: 0.9679
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- Recall: 0.9610
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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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: 0.2
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.2471 | 1.0 | 3125 | 0.2004 | 0.9487 | 0.9474 | 0.9710 | 0.9250 |
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| 0.2029 | 2.0 | 6250 | 0.1715 | 0.9603 | 0.9600 | 0.9664 | 0.9537 |
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| 0.0631 | 3.0 | 9375 | 0.2049 | 0.9566 | 0.9555 | 0.9793 | 0.9329 |
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| 0.0432 | 4.0 | 12500 | 0.1906 | 0.9646 | 0.9645 | 0.9679 | 0.9610 |
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### Framework versions
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- Transformers 4.39.2
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- Pytorch 2.2.0+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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version https://git-lfs.github.com/spec/v1
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-
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size 1740304440
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version https://git-lfs.github.com/spec/v1
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size 1740304440
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