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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mdeberta-hate-final
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mdeberta-hate-final
This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6223
- Accuracy: 0.7424
- Precision: 0.7410
- Recall: 0.7424
- F1: 0.7363
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 296 | 0.5309 | 0.7519 | 0.7685 | 0.7519 | 0.7357 |
| 0.5358 | 2.0 | 592 | 0.5228 | 0.7510 | 0.7663 | 0.7510 | 0.7351 |
| 0.5358 | 3.0 | 888 | 0.5565 | 0.7510 | 0.7513 | 0.7510 | 0.7438 |
| 0.4295 | 4.0 | 1184 | 0.5639 | 0.7481 | 0.7488 | 0.7481 | 0.7403 |
| 0.4295 | 5.0 | 1480 | 0.5941 | 0.7510 | 0.7531 | 0.7510 | 0.7423 |
| 0.3701 | 6.0 | 1776 | 0.6223 | 0.7424 | 0.7410 | 0.7424 | 0.7363 |
### Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1
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