arunaramm7
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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
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: my_awesome_wnut_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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should probably proofread and complete it, then remove this comment. -->
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# my_awesome_wnut_model
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1248
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- Precision: 0.0122
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- Recall: 0.0556
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- F1: 0.0200
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- Accuracy: 0.1324
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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: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 7 | 2.1248 | 0.0122 | 0.0556 | 0.0200 | 0.1324 |
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| No log | 2.0 | 14 | 2.1248 | 0.0122 | 0.0556 | 0.0200 | 0.1324 |
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### Framework versions
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- Transformers 4.39.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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runs/Mar30_12-07-34_a08fa3fb536a/events.out.tfevents.1711802519.a08fa3fb536a.1792.3
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version https://git-lfs.github.com/spec/v1
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oid sha256:2a802d94780f3695b12065cea91927f27b90970ec8573789ecc7d4e5a80e9633
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size 551
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