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---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
datasets:
- scicite
metrics:
- accuracy
model-index:
- name: Scicite_classification_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: scicite
type: scicite
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9224890829694323
---
<!-- 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. -->
# Scicite_classification_model
This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4704
- Accuracy: 0.9225
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2493 | 1.0 | 513 | 0.2034 | 0.9214 |
| 0.1777 | 2.0 | 1026 | 0.1942 | 0.9247 |
| 0.1385 | 3.0 | 1539 | 0.2552 | 0.9247 |
| 0.1019 | 4.0 | 2052 | 0.2995 | 0.9258 |
| 0.0705 | 5.0 | 2565 | 0.3964 | 0.9181 |
| 0.0444 | 6.0 | 3078 | 0.4243 | 0.9203 |
| 0.0331 | 7.0 | 3591 | 0.4904 | 0.9192 |
| 0.0223 | 8.0 | 4104 | 0.4704 | 0.9225 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3