File size: 1,798 Bytes
37995bb |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- inspec
metrics:
- f1
model-index:
- name: bert-finetuned-inspec
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: inspec
type: inspec
args: extraction
metrics:
- name: F1
type: f1
value: 0.30353331752430635
---
<!-- 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. -->
# bert-finetuned-inspec
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the inspec dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3055
- F1: 0.3035
## 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: 8
- eval_batch_size: 8
- 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3323 | 1.0 | 125 | 0.2799 | 0.1521 |
| 0.2563 | 2.0 | 250 | 0.2638 | 0.2230 |
| 0.2179 | 3.0 | 375 | 0.2689 | 0.2607 |
| 0.1809 | 4.0 | 500 | 0.2807 | 0.3122 |
| 0.1545 | 5.0 | 625 | 0.3055 | 0.3035 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
|