---
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
model-index:
- name: left_as_train_context_roberta-large_20e
  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. -->

# left_as_train_context_roberta-large_20e

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0530
- Val Accuracy: 0.7598
- Val Precision Macro: 0.7129
- Val Recall Macro: 0.7027
- Val F1 Macro: 0.7066
- Val Precision Weighted: 0.7605
- Val Recall Weighted: 0.7598
- Val F1 Weighted: 0.7595

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Val Accuracy | Val Precision Macro | Val Recall Macro | Val F1 Macro | Val Precision Weighted | Val Recall Weighted | Val F1 Weighted |
|:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------------:|:----------------:|:------------:|:----------------------:|:-------------------:|:---------------:|
| 0.4664        | 1.0   | 3630  | 0.6205          | 0.7544       | 0.7032              | 0.7108           | 0.7050       | 0.7625                 | 0.7544              | 0.7564          |
| 0.3597        | 2.0   | 7260  | 0.7307          | 0.7556       | 0.6982              | 0.7237           | 0.7093       | 0.7639                 | 0.7556              | 0.7587          |
| 0.2864        | 3.0   | 10890 | 0.8032          | 0.7509       | 0.6944              | 0.7157           | 0.7035       | 0.7605                 | 0.7509              | 0.7542          |
| 0.2149        | 4.0   | 14520 | 1.0851          | 0.7581       | 0.7066              | 0.7070           | 0.7061       | 0.7609                 | 0.7581              | 0.7588          |
| 0.182         | 5.0   | 18150 | 1.3747          | 0.7503       | 0.6907              | 0.7128           | 0.7004       | 0.7590                 | 0.7503              | 0.7535          |
| 0.1306        | 6.0   | 21780 | 1.7668          | 0.7444       | 0.7013              | 0.6941           | 0.6936       | 0.7534                 | 0.7444              | 0.7456          |
| 0.1116        | 7.0   | 25410 | 1.7892          | 0.7631       | 0.7199              | 0.6947           | 0.7046       | 0.7617                 | 0.7631              | 0.7612          |
| 0.0915        | 8.0   | 29040 | 2.0678          | 0.7565       | 0.7064              | 0.6918           | 0.6979       | 0.7551                 | 0.7565              | 0.7553          |
| 0.0696        | 9.0   | 32670 | 2.2576          | 0.7554       | 0.7103              | 0.6981           | 0.7019       | 0.7582                 | 0.7554              | 0.7553          |
| 0.0427        | 10.0  | 36300 | 2.2779          | 0.7588       | 0.7117              | 0.6998           | 0.7046       | 0.7589                 | 0.7588              | 0.7582          |
| 0.046         | 11.0  | 39930 | 2.4922          | 0.7580       | 0.7066              | 0.7004           | 0.7030       | 0.7581                 | 0.7580              | 0.7578          |
| 0.0242        | 12.0  | 43560 | 2.6629          | 0.7623       | 0.7150              | 0.7034           | 0.7085       | 0.7612                 | 0.7623              | 0.7615          |
| 0.0251        | 13.0  | 47190 | 2.7028          | 0.7527       | 0.7031              | 0.6977           | 0.6997       | 0.7538                 | 0.7527              | 0.7528          |
| 0.0214        | 14.0  | 50820 | 2.7458          | 0.7572       | 0.7104              | 0.7021           | 0.7046       | 0.7599                 | 0.7572              | 0.7574          |
| 0.0256        | 15.0  | 54450 | 2.7886          | 0.7552       | 0.7045              | 0.7036           | 0.7032       | 0.7582                 | 0.7552              | 0.7560          |
| 0.0134        | 16.0  | 58080 | 2.9100          | 0.7583       | 0.7077              | 0.7005           | 0.7036       | 0.7582                 | 0.7583              | 0.7580          |
| 0.0109        | 17.0  | 61710 | 2.8942          | 0.7599       | 0.7137              | 0.6963           | 0.7038       | 0.7580                 | 0.7599              | 0.7584          |
| 0.0087        | 18.0  | 65340 | 2.9562          | 0.7602       | 0.7146              | 0.7019           | 0.7072       | 0.7599                 | 0.7602              | 0.7595          |
| 0.0019        | 19.0  | 68970 | 3.0273          | 0.7589       | 0.7145              | 0.6999           | 0.7051       | 0.7602                 | 0.7589              | 0.7584          |
| 0.0043        | 20.0  | 72600 | 3.0530          | 0.7598       | 0.7129              | 0.7027           | 0.7066       | 0.7605                 | 0.7598              | 0.7595          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2