File size: 1,776 Bytes
b3fb173 0f3faa3 b3fb173 0f3faa3 b3fb173 0f3faa3 b3fb173 0f3faa3 b3fb173 | 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 | ---
license: mit
base_model: deepset/gbert-base
tags:
- generated_from_trainer
model-index:
- name: gbert-base-finetuned-twitter
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. -->
# gbert-base-finetuned-twitter
This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7380
## 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: 192
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.194 | 1.0 | 4180 | 1.9622 |
| 2.0075 | 2.0 | 8360 | 1.8813 |
| 1.9429 | 3.0 | 12540 | 1.8339 |
| 1.8985 | 4.0 | 16720 | 1.8057 |
| 1.8676 | 5.0 | 20900 | 1.7801 |
| 1.8446 | 6.0 | 25080 | 1.7793 |
| 1.829 | 7.0 | 29260 | 1.7580 |
| 1.815 | 8.0 | 33440 | 1.7445 |
| 1.8048 | 9.0 | 37620 | 1.7319 |
| 1.7997 | 10.0 | 41800 | 1.7331 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
|