File size: 2,229 Bytes
c72bcdb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SCIFACT_inference_model
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. -->
# SCIFACT_inference_model
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2496
- Accuracy: 0.8819
## 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: 1e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 378 | 1.0485 | 0.4724 |
| 1.0382 | 2.0 | 756 | 1.3964 | 0.6063 |
| 0.835 | 3.0 | 1134 | 0.9168 | 0.8268 |
| 0.6801 | 4.0 | 1512 | 0.7524 | 0.8425 |
| 0.6801 | 5.0 | 1890 | 1.0672 | 0.8346 |
| 0.4291 | 6.0 | 2268 | 0.9599 | 0.8425 |
| 0.2604 | 7.0 | 2646 | 0.8691 | 0.8661 |
| 0.1932 | 8.0 | 3024 | 1.3162 | 0.8268 |
| 0.1932 | 9.0 | 3402 | 1.3200 | 0.8583 |
| 0.0974 | 10.0 | 3780 | 1.1566 | 0.8740 |
| 0.1051 | 11.0 | 4158 | 1.1568 | 0.8819 |
| 0.0433 | 12.0 | 4536 | 1.2013 | 0.8661 |
| 0.0433 | 13.0 | 4914 | 1.1557 | 0.8819 |
| 0.034 | 14.0 | 5292 | 1.3044 | 0.8661 |
| 0.0303 | 15.0 | 5670 | 1.2496 | 0.8819 |
### Framework versions
- Transformers 4.34.1
- Pytorch 1.13.1+cu116
- Datasets 2.14.6
- Tokenizers 0.14.1
|