File size: 1,945 Bytes
0d70e30 | 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 | ---
library_name: transformers
license: apache-2.0
base_model: google/mobilebert-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: google_mobilebert-uncased_fold_6
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. -->
# google_mobilebert-uncased_fold_6
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1170
- Accuracy: 0.9588
- F1: 0.9548
- Precision: 0.9603
- Recall: 0.9493
## 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: 40
- eval_batch_size: 40
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1319 | 1.0 | 15481 | 0.1306 | 0.9502 | 0.9452 | 0.9520 | 0.9386 |
| 0.0944 | 2.0 | 30962 | 0.1145 | 0.9567 | 0.9525 | 0.9573 | 0.9477 |
| 0.0772 | 3.0 | 46443 | 0.1170 | 0.9588 | 0.9548 | 0.9603 | 0.9493 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2
|