File size: 2,937 Bytes
403c1fd |
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 80 81 |
---
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-tiny2-odonata-extended-ner
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. -->
# rubert-tiny2-odonata-extended-ner
This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0226
- Precision: 0.5313
- Recall: 0.551
- F1: 0.5410
- Accuracy: 0.9930
## 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: 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 32 | 0.1425 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 2.0 | 64 | 0.0643 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 3.0 | 96 | 0.0604 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 4.0 | 128 | 0.0575 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 5.0 | 160 | 0.0523 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 6.0 | 192 | 0.0427 | 0.0 | 0.0 | 0.0 | 0.9910 |
| No log | 7.0 | 224 | 0.0330 | 0.7753 | 0.069 | 0.1267 | 0.9913 |
| No log | 8.0 | 256 | 0.0288 | 0.6309 | 0.376 | 0.4712 | 0.9921 |
| No log | 9.0 | 288 | 0.0264 | 0.6145 | 0.373 | 0.4642 | 0.9924 |
| No log | 10.0 | 320 | 0.0251 | 0.5489 | 0.432 | 0.4835 | 0.9926 |
| No log | 11.0 | 352 | 0.0242 | 0.5354 | 0.484 | 0.5084 | 0.9927 |
| No log | 12.0 | 384 | 0.0235 | 0.5393 | 0.515 | 0.5269 | 0.9928 |
| No log | 13.0 | 416 | 0.0230 | 0.5310 | 0.54 | 0.5354 | 0.9929 |
| No log | 14.0 | 448 | 0.0228 | 0.5287 | 0.553 | 0.5406 | 0.9930 |
| No log | 15.0 | 480 | 0.0226 | 0.5313 | 0.551 | 0.5410 | 0.9930 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.19.2
- Tokenizers 0.19.1
|