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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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- 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: WITHINAPPS_NDD-petclinic_test-content-CWAdj
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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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# WITHINAPPS_NDD-petclinic_test-content-CWAdj
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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: 0.0000
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- Accuracy: 1.0
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- F1: 1.0
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- Precision: 1.0
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- Recall: 1.0
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 5
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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 | 69 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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| No log | 2.0 | 138 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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| No log | 3.0 | 207 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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| No log | 4.0 | 276 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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| No log | 5.0 | 345 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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