---
license: apache-2.0
datasets:
- Jsevisal/gesture_pred
metrics:
- precision
- recall
- f1
- accuracy
widget:
- text: I'm fine. Who is this?
- text: You can't take anything seriously.
- text: In the end he''s going to croak, isn''t he?
pipeline_tag: token-classification
base_model: elastic/distilbert-base-cased-finetuned-conll03-english
model-index:
- name: distilbert-gest-pred-seqeval-partialmatch
  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. -->

# distilbert-gest-pred-seqeval-partialmatch

This model is a fine-tuned version of [elastic/distilbert-base-cased-finetuned-conll03-english](https://huggingface.co/elastic/distilbert-base-cased-finetuned-conll03-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7300
- Precision: 0.8116
- Recall: 0.6988
- F1: 0.7337
- Accuracy: 0.8082

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.8684        | 1.0   | 147  | 1.1962          | 0.3713    | 0.4095 | 0.3845 | 0.7100   |
| 0.9616        | 2.0   | 294  | 0.8900          | 0.6151    | 0.5556 | 0.5459 | 0.7594   |
| 0.696         | 3.0   | 441  | 0.7715          | 0.5896    | 0.5636 | 0.5634 | 0.7848   |
| 0.5283        | 4.0   | 588  | 0.7300          | 0.8116    | 0.6988 | 0.7337 | 0.8082   |
| 0.4079        | 5.0   | 735  | 0.7423          | 0.7973    | 0.6971 | 0.7258 | 0.8134   |
| 0.309         | 6.0   | 882  | 0.8589          | 0.8034    | 0.6935 | 0.7185 | 0.7965   |
| 0.2629        | 7.0   | 1029 | 0.8160          | 0.8076    | 0.6955 | 0.7268 | 0.7958   |
| 0.2059        | 8.0   | 1176 | 0.8178          | 0.8116    | 0.7130 | 0.7382 | 0.8127   |
| 0.1701        | 9.0   | 1323 | 0.8471          | 0.7981    | 0.7214 | 0.7365 | 0.8101   |
| 0.1574        | 10.0  | 1470 | 0.8515          | 0.7956    | 0.7216 | 0.7363 | 0.8088   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2