Training in progress, step 7000

README.md

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----
-license: mit
-tags:
-- generated_from_trainer
-metrics:
-- precision
-- recall
-- f1
-- accuracy
-model-index:
-- name: xlm-roberta-base-finetuned-pos
-  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-pos
-
-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: 0.0827
-- Precision: 0.9738
-- Recall: 0.9748
-- F1: 0.9743
-- Accuracy: 0.9769
-
-## 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: 3
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1627        | 1.0   | 1583 | 0.1273          | 0.9584    | 0.9619 | 0.9601 | 0.9641   |
-| 0.0984        | 2.0   | 3166 | 0.0909          | 0.9704    | 0.9722 | 0.9713 | 0.9743   |
-| 0.0747        | 3.0   | 4749 | 0.0827          | 0.9738    | 0.9748 | 0.9743 | 0.9769   |
-
-
-### Framework versions
-
-- Transformers 4.27.3
-- Pytorch 1.13.1+cu116
-- Datasets 2.10.1
-- Tokenizers 0.13.2

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