End of training
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README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased-finetuned-sst-2-english
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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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model-index:
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- name: finetuning-sentiment-model-5000-samples
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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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# finetuning-sentiment-model-5000-samples
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This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3309
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- Accuracy: 0.9156
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- F1: 0.9436
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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: 1e-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: linear
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 254 | 0.2906 | 0.8844 | 0.9263 |
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| 0.2482 | 2.0 | 508 | 0.2648 | 0.9067 | 0.9371 |
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| 0.2482 | 3.0 | 762 | 0.3114 | 0.92 | 0.9472 |
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| 0.1236 | 4.0 | 1016 | 0.3309 | 0.9156 | 0.9436 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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runs/Jun17_00-38-56_7d4fc80acb3e/events.out.tfevents.1718585284.7d4fc80acb3e.2434.3
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version https://git-lfs.github.com/spec/v1
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oid sha256:3c78dac06c7f691385aaf1054cbdf567e080f04a66a1740489bec1df14377c7f
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size 457
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