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library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cohere_generated_abstracts_roberta
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. -->
# cohere_generated_abstracts_roberta
This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0078 | 0.0838 | 100 | 0.0029 | 0.9996 |
| 0.0036 | 0.1676 | 200 | 0.0053 | 0.9992 |
| 0.0064 | 0.2515 | 300 | 0.0012 | 0.9999 |
| 0.002 | 0.3353 | 400 | 0.0028 | 0.9996 |
| 0.0019 | 0.4191 | 500 | 0.0009 | 0.9999 |
| 0.0014 | 0.5029 | 600 | 0.0026 | 0.9998 |
| 0.0003 | 0.5868 | 700 | 0.0012 | 0.9999 |
| 0.0017 | 0.6706 | 800 | 0.0000 | 1.0 |
| 0.0015 | 0.7544 | 900 | 0.0000 | 1.0 |
| 0.0019 | 0.8382 | 1000 | 0.0007 | 0.9999 |
| 0.0033 | 0.9220 | 1100 | 0.0048 | 0.9994 |
| 0.0013 | 1.0059 | 1200 | 0.0001 | 1.0 |
| 0.0032 | 1.0897 | 1300 | 0.0015 | 0.9998 |
| 0.0013 | 1.1735 | 1400 | 0.0000 | 1.0 |
| 0.0 | 1.2573 | 1500 | 0.0000 | 1.0 |
| 0.0 | 1.3412 | 1600 | 0.0000 | 1.0 |
| 0.0 | 1.4250 | 1700 | 0.0000 | 1.0 |
| 0.0003 | 1.5088 | 1800 | 0.0023 | 0.9996 |
| 0.0005 | 1.5926 | 1900 | 0.0000 | 1.0 |
| 0.0 | 1.6764 | 2000 | 0.0000 | 1.0 |
| 0.0 | 1.7603 | 2100 | 0.0000 | 1.0 |
| 0.0 | 1.8441 | 2200 | 0.0000 | 1.0 |
| 0.0 | 1.9279 | 2300 | 0.0000 | 1.0 |
| 0.0 | 2.0117 | 2400 | 0.0000 | 1.0 |
| 0.0 | 2.0956 | 2500 | 0.0000 | 1.0 |
| 0.0 | 2.1794 | 2600 | 0.0000 | 1.0 |
| 0.0 | 2.2632 | 2700 | 0.0000 | 1.0 |
| 0.0 | 2.3470 | 2800 | 0.0000 | 1.0 |
| 0.0 | 2.4308 | 2900 | 0.0000 | 1.0 |
| 0.0 | 2.5147 | 3000 | 0.0000 | 1.0 |
| 0.0 | 2.5985 | 3100 | 0.0000 | 1.0 |
| 0.0 | 2.6823 | 3200 | 0.0000 | 1.0 |
| 0.0 | 2.7661 | 3300 | 0.0000 | 1.0 |
| 0.0 | 2.8500 | 3400 | 0.0000 | 1.0 |
| 0.0 | 2.9338 | 3500 | 0.0000 | 1.0 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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