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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert_finetuned_claimdecomp
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. -->
# distilbert_finetuned_claimdecomp
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 9.3205
- Accuracy: 0.335
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 30000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0064 | 50.0 | 5000 | 5.7963 | 0.375 |
| 0.0 | 100.0 | 10000 | 7.2917 | 0.36 |
| 0.0 | 150.0 | 15000 | 7.0473 | 0.33 |
| 0.0 | 200.0 | 20000 | 8.0988 | 0.31 |
| 0.0 | 250.0 | 25000 | 8.8824 | 0.325 |
| 0.0 | 300.0 | 30000 | 9.3205 | 0.335 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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