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---
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta_base_amazon
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_amazon
This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7775
- Accuracy: 0.7826
- F1 Macro: 0.7137
- F1 Micro: 0.7826
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.2364 | 0.26 | 50 | 1.9915 | 0.5487 | 0.3934 | 0.5487 |
| 1.4061 | 0.53 | 100 | 1.3136 | 0.6449 | 0.5030 | 0.6449 |
| 1.1502 | 0.79 | 150 | 1.1137 | 0.6937 | 0.5697 | 0.6937 |
| 1.0396 | 1.05 | 200 | 0.9888 | 0.7358 | 0.6345 | 0.7358 |
| 0.86 | 1.32 | 250 | 0.9200 | 0.7437 | 0.6560 | 0.7437 |
| 0.9646 | 1.58 | 300 | 0.8704 | 0.7497 | 0.6626 | 0.7497 |
| 0.8749 | 1.84 | 350 | 0.8367 | 0.7708 | 0.6960 | 0.7708 |
| 0.8031 | 2.11 | 400 | 0.8125 | 0.7767 | 0.7069 | 0.7767 |
| 0.7728 | 2.37 | 450 | 0.7912 | 0.7787 | 0.7085 | 0.7787 |
| 0.7164 | 2.63 | 500 | 0.7829 | 0.7793 | 0.7068 | 0.7793 |
| 0.7533 | 2.89 | 550 | 0.7775 | 0.7826 | 0.7137 | 0.7826 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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