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: microsoft/deberta-v3-large
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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: deberta-v3-large_v1_no_entities_with_context
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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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# deberta-v3-large_v1_no_entities_with_context
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0256
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- Accuracy: 0.0045
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- F1: 0.0090
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- Precision: 0.0045
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- Recall: 1.0
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- Learning Rate: 0.0
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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: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Rate |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
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| 0.0438 | 1.0 | 809 | 0.0270 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0002 |
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| 0.0306 | 2.0 | 1618 | 0.0265 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0001 |
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| 0.0323 | 3.0 | 2427 | 0.0255 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 5e-05 |
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| 0.0298 | 4.0 | 3236 | 0.0256 | 0.0045 | 0.0090 | 0.0045 | 1.0 | 0.0 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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