File size: 1,726 Bytes
15f45b9 0062172 15f45b9 0062172 15f45b9 5405081 15f45b9 abf5057 15f45b9 0062172 15f45b9 abf5057 15f45b9 abf5057 15f45b9 0062172 15f45b9 0062172 15f45b9 0062172 15f45b9 5405081 |
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 |
---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-trainer
results: []
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. -->
# test-trainer
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the cryptocurrency dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2337
- Accuracy: 0.9169
## Model description
intent search detection :
Navigational: Users want to find a specific page (e.g., “reddit login”)
Informational: Users want to learn more about something (e.g., “what is seo”)
Commercial: Users want to do research before making a purchase decision (e.g., “best coffee maker”)
Transactional: Users want to complete a specific action, usually a purchase (e.g., “buy subaru forester”)
### 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3629 | 1.0 | 14391 | 0.3249 | 0.8866 |
| 0.313 | 2.0 | 28782 | 0.2640 | 0.9067 |
| 0.2723 | 3.0 | 43173 | 0.2337 | 0.9169 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1 |