File size: 2,295 Bytes
edbbaaf 83fe4a1 edbbaaf 83fe4a1 edbbaaf c824d23 edbbaaf c824d23 edbbaaf c824d23 edbbaaf c824d23 edbbaaf d0f8270 edbbaaf c824d23 edbbaaf dc85824 c824d23 edbbaaf c824d23 edbbaaf ef2154c c824d23 edbbaaf d0f8270 edbbaaf d0f8270 edbbaaf |
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 82 83 84 85 86 87 88 89 90 91 92 93 94 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ner
type: ner
config: indian_names
split: train
args: indian_names
metrics:
- name: Precision
type: precision
value: 1.0
- name: Recall
type: recall
value: 1.0
- name: F1
type: f1
value: 1.0
- name: Accuracy
type: accuracy
value: 1.0
---
<!-- 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. -->
# my_awesome_wnut_model
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 344 | 0.0008 | 0.9995 | 0.9994 | 0.9994 | 0.9997 |
| 0.0027 | 2.0 | 688 | 0.0008 | 0.9994 | 0.9993 | 0.9994 | 0.9996 |
| 0.0016 | 3.0 | 1032 | 0.0001 | 1.0000 | 0.9999 | 0.9999 | 1.0000 |
| 0.0016 | 4.0 | 1376 | 0.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 0.0003 | 5.0 | 1720 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|