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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
base_model: distilroberta-base
model-index:
- name: distilroberta-base-mic
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. -->
# distilroberta-base-mic
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3435
- Accuracy: 0.9104
- F1: 0.9103
## 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: 8.748413056668156e-05
- train_batch_size: 200
- eval_batch_size: 200
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 120 | 0.2830 | 0.8804 | 0.8797 |
| No log | 2.0 | 240 | 0.2398 | 0.9046 | 0.9046 |
| No log | 3.0 | 360 | 0.3474 | 0.8959 | 0.8954 |
| No log | 4.0 | 480 | 0.3435 | 0.9104 | 0.9103 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
|