File size: 2,224 Bytes
fe4bc8e 8004794 fe4bc8e 8004794 fe4bc8e 47bf57c fe4bc8e 47bf57c fe4bc8e 47bf57c 8004794 |
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 76 77 78 79 |
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: distilroberta-tcfd-disclosure
results: []
datasets:
- rexarski/TCFD_disclosure
language:
- en
---
<!-- 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-tcfd-disclosure
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co./distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8681
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 5 | 2.3837 |
| 2.3918 | 2.0 | 10 | 2.3787 |
| 2.3918 | 3.0 | 15 | 2.3704 |
| 2.3754 | 4.0 | 20 | 2.3623 |
| 2.3754 | 5.0 | 25 | 2.3396 |
| 2.2976 | 6.0 | 30 | 2.2599 |
| 2.2976 | 7.0 | 35 | 2.1095 |
| 2.0439 | 8.0 | 40 | 2.0184 |
| 2.0439 | 9.0 | 45 | 1.9059 |
| 1.6799 | 10.0 | 50 | 1.8469 |
| 1.6799 | 11.0 | 55 | 1.8089 |
| 1.2948 | 12.0 | 60 | 1.7263 |
| 1.2948 | 13.0 | 65 | 1.7250 |
| 0.9621 | 14.0 | 70 | 1.8106 |
| 0.9621 | 15.0 | 75 | 1.8073 |
| 0.7356 | 16.0 | 80 | 1.8681 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3 |