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---
library_name: transformers
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
model-index:
- name: XLtolli
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. -->
# XLtolli
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co./xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4737
- eval_accuracy: 0.8635
- eval_f1: 0.8634
- eval_runtime: 1328.1503
- eval_samples_per_second: 78.779
- eval_steps_per_second: 0.788
- epoch: 1.5180
- step: 3000
## 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: 100
- eval_batch_size: 100
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 300
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 7
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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