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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_data-AmazonScience_massive_all_1_1_delta
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: 0.051647811116576486
- name: F1
type: f1
value: 0.0016647904742274576
---
<!-- 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_data-AmazonScience_massive_all_1_1_delta
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: 3.8343
- Accuracy: 0.0516
- F1: 0.0017
## 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: 11213
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 3.7591 | 0.27 | 5000 | 3.7340 | 0.0644 | 0.0021 |
| 3.7519 | 0.53 | 10000 | 3.7681 | 0.0620 | 0.0020 |
| 3.7417 | 0.8 | 15000 | 3.8022 | 0.0620 | 0.0020 |
| 3.7237 | 1.07 | 20000 | 3.8134 | 0.0516 | 0.0017 |
| 3.7217 | 1.34 | 25000 | 3.8412 | 0.0516 | 0.0017 |
| 3.7172 | 1.6 | 30000 | 3.8343 | 0.0516 | 0.0017 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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