---
license: apache-2.0
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?
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-gest-pred-seqeval-partialmatch
  results: []
datasets:
- Jsevisal/gesture_pred
language:
- en
pipeline_tag: token-classification
---

<!-- 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: 0.711886
- Precision: 0.832250
- Recall: 0.832250
- F1: 0.832250	
- Accuracy: 0.817295

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.9119        | 1.0   | 147  | 1.1835          | 0.7412    | 0.7412 | 0.7412 | 0.7204   |
| 0.9884        | 2.0   | 294  | 0.8666          | 0.7906    | 0.7906 | 0.7906 | 0.7731   |
| 0.7238        | 3.0   | 441  | 0.7754          | 0.8056    | 0.8056 | 0.8056 | 0.7906   |
| 0.5564        | 4.0   | 588  | 0.7129          | 0.8114    | 0.8114 | 0.8114 | 0.7965   |
| 0.4343        | 5.0   | 735  | 0.7119          | 0.8322    | 0.8322 | 0.8322 | 0.8173   |
| 0.3261        | 6.0   | 882  | 0.7545          | 0.8179    | 0.8179 | 0.8179 | 0.8075   |
| 0.2688        | 7.0   | 1029 | 0.7760          | 0.8121    | 0.8121 | 0.8121 | 0.8010   |
| 0.2178        | 8.0   | 1176 | 0.7744          | 0.8283    | 0.8283 | 0.8283 | 0.8179   |
| 0.1822        | 9.0   | 1323 | 0.7894          | 0.8322    | 0.8322 | 0.8322 | 0.8231   |
| 0.1636        | 10.0  | 1470 | 0.7941          | 0.8316    | 0.8316 | 0.8316 | 0.8218   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2