Training complete
Browse files
README.md
ADDED
|
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
library_name: transformers
|
| 3 |
+
license: mit
|
| 4 |
+
base_model: cjber/reddit-ner-place_names
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
metrics:
|
| 8 |
+
- precision
|
| 9 |
+
- recall
|
| 10 |
+
- f1
|
| 11 |
+
- accuracy
|
| 12 |
+
- wer
|
| 13 |
+
model-index:
|
| 14 |
+
- name: reddit-ner-place_names-finetuned
|
| 15 |
+
results: []
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 19 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 20 |
+
|
| 21 |
+
# reddit-ner-place_names-finetuned
|
| 22 |
+
|
| 23 |
+
This model is a fine-tuned version of [cjber/reddit-ner-place_names](https://huggingface.co/cjber/reddit-ner-place_names) on an unknown dataset.
|
| 24 |
+
It achieves the following results on the evaluation set:
|
| 25 |
+
- Loss: 0.0301
|
| 26 |
+
- Precision: 0.8010
|
| 27 |
+
- Recall: 0.8406
|
| 28 |
+
- F1: 0.8203
|
| 29 |
+
- Accuracy: 0.9929
|
| 30 |
+
- Wer: 0.0071
|
| 31 |
+
|
| 32 |
+
## Model description
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Intended uses & limitations
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training and evaluation data
|
| 41 |
+
|
| 42 |
+
More information needed
|
| 43 |
+
|
| 44 |
+
## Training procedure
|
| 45 |
+
|
| 46 |
+
### Training hyperparameters
|
| 47 |
+
|
| 48 |
+
The following hyperparameters were used during training:
|
| 49 |
+
- learning_rate: 2e-05
|
| 50 |
+
- train_batch_size: 8
|
| 51 |
+
- eval_batch_size: 8
|
| 52 |
+
- seed: 42
|
| 53 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 54 |
+
- lr_scheduler_type: linear
|
| 55 |
+
- num_epochs: 5
|
| 56 |
+
|
| 57 |
+
### Training results
|
| 58 |
+
|
| 59 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Wer |
|
| 60 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|
|
| 61 |
+
| 0.024 | 1.0 | 1535 | 0.0214 | 0.7826 | 0.8414 | 0.8109 | 0.9924 | 0.0075 |
|
| 62 |
+
| 0.0173 | 2.0 | 3070 | 0.0203 | 0.7865 | 0.8526 | 0.8182 | 0.9928 | 0.0072 |
|
| 63 |
+
| 0.0109 | 3.0 | 4605 | 0.0234 | 0.8166 | 0.8351 | 0.8257 | 0.9930 | 0.0070 |
|
| 64 |
+
| 0.0078 | 4.0 | 6140 | 0.0264 | 0.8179 | 0.8259 | 0.8219 | 0.9930 | 0.0070 |
|
| 65 |
+
| 0.005 | 5.0 | 7675 | 0.0301 | 0.8010 | 0.8406 | 0.8203 | 0.9929 | 0.0071 |
|
| 66 |
+
|
| 67 |
+
|
| 68 |
+
### Framework versions
|
| 69 |
+
|
| 70 |
+
- Transformers 4.45.2
|
| 71 |
+
- Pytorch 2.4.1+cu121
|
| 72 |
+
- Datasets 3.0.1
|
| 73 |
+
- Tokenizers 0.20.1
|