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README.md
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- generated_from_trainer
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datasets:
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- rotten_tomatoes_movie_review
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model-index:
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- name: my_distilbert_model
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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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# my_distilbert_model
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the rotten_tomatoes_movie_review dataset.
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## Model description
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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:
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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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| No log | 1.0 | 267 | 0.
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### Framework versions
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- generated_from_trainer
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datasets:
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- rotten_tomatoes_movie_review
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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: my_distilbert_model
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: rotten_tomatoes_movie_review
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type: rotten_tomatoes_movie_review
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config: default
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split: test
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8480300187617261
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- name: F1
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type: f1
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value: 0.8480214592727926
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- name: Precision
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type: precision
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value: 0.8481084411583488
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- name: Recall
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type: recall
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value: 0.8480300187617261
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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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# my_distilbert_model
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the rotten_tomatoes_movie_review dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4452
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- Accuracy: 0.8480
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- F1: 0.8480
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- Precision: 0.8481
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- Recall: 0.8480
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## Model description
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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: 3
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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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| No log | 1.0 | 267 | 0.4094 | 0.8246 | 0.8241 | 0.8281 | 0.8246 |
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| 0.3518 | 2.0 | 534 | 0.4000 | 0.8508 | 0.8508 | 0.8510 | 0.8508 |
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| 0.3518 | 3.0 | 801 | 0.4452 | 0.8480 | 0.8480 | 0.8481 | 0.8480 |
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### Framework versions
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