End of training
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README.md
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---
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license: mit
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base_model: xlnet-base-cased
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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: xlnet-base-cased-tweets
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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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# xlnet-base-cased-tweets
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2094
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- Accuracy: 0.9236
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- F1: 0.9553
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- Precision: 0.9531
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- Recall: 0.9575
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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: 16
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- eval_batch_size: 8
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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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| 0.2551 | 1.0 | 642 | 0.2172 | 0.9037 | 0.9443 | 0.9311 | 0.9579 |
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| 0.1981 | 2.0 | 1284 | 0.2366 | 0.9135 | 0.9500 | 0.9349 | 0.9657 |
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| 0.1513 | 3.0 | 1926 | 0.2094 | 0.9236 | 0.9553 | 0.9531 | 0.9575 |
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### Framework versions
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- Transformers 4.43.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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runs/Jul03_22-41-33_raul-MS-7B98/events.out.tfevents.1720064500.raul-MS-7B98.7659.0
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 7495
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