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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-finetuned-chunking
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. -->
# roberta-large-finetuned-chunking
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4192
- Precision: 0.3222
- Recall: 0.3161
- F1: 0.3191
- Accuracy: 0.8632
## 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: 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: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0373 | 1.0 | 2498 | 0.9545 | 0.3166 | 0.2545 | 0.2822 | 0.8656 |
| 0.0045 | 2.0 | 4996 | 1.1324 | 0.2667 | 0.3142 | 0.2885 | 0.8525 |
| 0.0022 | 3.0 | 7494 | 1.3138 | 0.3349 | 0.3097 | 0.3218 | 0.8672 |
| 0.0015 | 4.0 | 9992 | 1.3454 | 0.3261 | 0.3260 | 0.3260 | 0.8647 |
| 0.0014 | 5.0 | 12490 | 1.3640 | 0.3064 | 0.3126 | 0.3095 | 0.8603 |
| 0.0008 | 6.0 | 14988 | 1.4192 | 0.3222 | 0.3161 | 0.3191 | 0.8632 |
### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1