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update model card README.md
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README.md
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---
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license: apache-2.0
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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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- precision
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- recall
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- f1
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model-index:
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- name: twitter-data-distilbert-base-uncased-sentiment-finetuned-memes
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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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# twitter-data-distilbert-base-uncased-sentiment-finetuned-memes
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2605
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- Accuracy: 0.9316
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- Precision: 0.9322
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- Recall: 0.9316
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- F1: 0.9317
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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: 64
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- eval_batch_size: 64
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.3463 | 1.0 | 1783 | 0.2966 | 0.9065 | 0.9079 | 0.9065 | 0.9066 |
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| 0.2601 | 2.0 | 3566 | 0.2526 | 0.9245 | 0.9254 | 0.9245 | 0.9244 |
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| 0.2228 | 3.0 | 5349 | 0.2355 | 0.9313 | 0.9327 | 0.9313 | 0.9314 |
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| 0.1997 | 4.0 | 7132 | 0.2243 | 0.9341 | 0.9354 | 0.9341 | 0.9342 |
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| 0.1779 | 5.0 | 8915 | 0.2254 | 0.9346 | 0.9354 | 0.9346 | 0.9345 |
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| 0.1642 | 6.0 | 10698 | 0.2355 | 0.9322 | 0.9329 | 0.9322 | 0.9323 |
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| 0.146 | 7.0 | 12481 | 0.2485 | 0.9302 | 0.9306 | 0.9302 | 0.9303 |
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| 0.1368 | 8.0 | 14264 | 0.2530 | 0.9296 | 0.9312 | 0.9296 | 0.9299 |
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| 0.1293 | 9.0 | 16047 | 0.2585 | 0.9317 | 0.9322 | 0.9317 | 0.9317 |
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| 0.121 | 10.0 | 17830 | 0.2605 | 0.9316 | 0.9322 | 0.9316 | 0.9317 |
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### Framework versions
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- Transformers 4.24.0.dev0
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- Pytorch 1.11.0+cu102
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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