1111_Rice 1112_Flours and other cereals 1113_Bread 1114_Other bakery products 1115_Pizza and quiche 1116_Pasta products and couscous 1117_Breakfast cereals 1118_Other cereal products 1121_Beef and veal 1122_Pork 1123_Lamb and goat 1124_Poultry 1125_Other meats 1126_Edible offal 1127_Dried, salted or smoked meat 1128_Other meat preparations 1131_Fresh or chilled fish 1132_Frozen fish 1133_Fresh or chilled seafood 1134_Frozen seafood 1135_Dried, smoked or salted fish and seafood 1136_Other preserved or processed fish and seafood-based preparations 1141_Fresh whole milk 1142_Fresh low fat milk 1143_Preserved milk 1144_Yoghurt 1145_Cheese and curd 1146_Other milk products 1147_Eggs 1151_Butter 1152_Margarine and other vegetable fats 1153_Olive oil 1154_Other edible oils 1155_Other edible animal fats 1161_Fresh or chilled fruit 1162_Frozen fruit 1163_Dried fruit and nuts 1164_Preserved fruit and fruit-based products 1171_Fresh or chilled vegetables other than potatoes and other tubers 1172_Frozen vegetables other than potatoes and other tubers 1173_Dried vegetables, other preserved or processed vegetables 1174_Potatoes 1175_Crisps 1176_Other tubers and products of tuber vegetables 1181_Sugar 1182_Jams, marmalades and honey 1183_Chocolate 1184_Confectionery products 1185_Edible ices and ice cream 1186_Artificial sugar substitutes 1191_Sauces, condiments 1192_Salt, spices and culinary herbs 1193_Baby food 1194_Ready-made meals 1199_Other food products n.e.c. 1211_Coffee 1212_Tea 1213_Cocoa and powdered chocolate 1221_Mineral or spring waters 1222_Soft drinks 1223_Fruit and vegetable juices 2111_Spirits and liqueurs 2112_Alcoholic soft drinks 2121_Wine from grapes 2122_Wine from other fruits 2123_Fortified wines 2124_Wine-based drinks 2131_Lager beer 2132_Other alcoholic beer 2133_Low and non-alcoholic beer 2134_Beer-based drinks 2201_Cigarettes 2202_Cigars 2203_Other tobacco products 9999_Non-Food
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-finetuned-ecoicop
  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. -->

# xlm-roberta-base-finetuned-ecoicop

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1685
- Acc: 0.9659

## 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Acc    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4224        | 1.0   | 2577  | 0.3612          | 0.9132 |
| 0.2313        | 2.0   | 5154  | 0.2510          | 0.9441 |
| 0.1746        | 3.0   | 7731  | 0.1928          | 0.9569 |
| 0.1325        | 4.0   | 10308 | 0.1731          | 0.9640 |
| 0.0946        | 5.0   | 12885 | 0.1685          | 0.9659 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
