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---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: all_1.1
split: validation
args: all_1.1
metrics:
- name: Accuracy
type: accuracy
value: 0.8472984221877483
- name: F1
type: f1
value: 0.8225956665149763
---
<!-- 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. -->
# scenario-TCR-XLMV-1_data-AmazonScience_massive_all_1_1
This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7886
- Accuracy: 0.8473
- F1: 0.8226
## 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-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 47
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.587 | 0.27 | 5000 | 0.7148 | 0.8166 | 0.7696 |
| 0.456 | 0.53 | 10000 | 0.6624 | 0.8415 | 0.8006 |
| 0.3711 | 0.8 | 15000 | 0.6803 | 0.8394 | 0.8064 |
| 0.2846 | 1.07 | 20000 | 0.7409 | 0.8406 | 0.8119 |
| 0.2698 | 1.34 | 25000 | 0.7120 | 0.8428 | 0.8129 |
| 0.2589 | 1.6 | 30000 | 0.7179 | 0.8478 | 0.8300 |
| 0.246 | 1.87 | 35000 | 0.7383 | 0.8455 | 0.8119 |
| 0.2079 | 2.14 | 40000 | 0.7911 | 0.8503 | 0.8162 |
| 0.2157 | 2.41 | 45000 | 0.7775 | 0.8434 | 0.8251 |
| 0.2111 | 2.67 | 50000 | 0.7737 | 0.8455 | 0.8196 |
| 0.2014 | 2.94 | 55000 | 0.7886 | 0.8473 | 0.8226 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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