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        README.md
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         @@ -9,21 +9,21 @@ metrics: 
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            - precision
         
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            - recall
         
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            model-index:
         
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            - name:  
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              results: []
         
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            ---
         
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            <!-- This model card has been generated automatically according to the information the Trainer had access to. You
         
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            #  
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            This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
         
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            It achieves the following results on the evaluation set:
         
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            - Loss: 0. 
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            - F1: 0. 
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            - Precision: 0. 
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            - Recall: 0. 
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            ## Model description
         
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         @@ -59,11 +59,11 @@ The following hyperparameters were used during training: 
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            | Training Loss | Epoch | Step  | Validation Loss | F1     | Precision | Recall |
         
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            ### Framework versions
         
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            - precision
         
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            - recall
         
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            model-index:
         
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            - name: roberta-base-multilingual-sentiment
         
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              results: []
         
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            ---
         
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            <!-- This model card has been generated automatically according to the information the Trainer had access to. You
         
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            should probably proofread and complete it, then remove this comment. -->
         
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            # roberta-base-multilingual-sentiment
         
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            This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
         
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            It achieves the following results on the evaluation set:
         
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            - Loss: 0.4341
         
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            - F1: 0.8169
         
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            - Precision: 0.8176
         
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            - Recall: 0.8163
         
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            ## Model description
         
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            | Training Loss | Epoch | Step  | Validation Loss | F1     | Precision | Recall |
         
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            |:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
         
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            | 0.893         | 1.0   | 3074  | 0.4333          | 0.8038 | 0.8076    | 0.8022 |
         
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            | 0.8335        | 2.0   | 6148  | 0.4180          | 0.8150 | 0.8152    | 0.8149 |
         
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            | 0.7149        | 3.0   | 9222  | 0.4238          | 0.8162 | 0.8168    | 0.8158 |
         
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            | 0.7298        | 4.0   | 12296 | 0.4258          | 0.8168 | 0.8178    | 0.8160 |
         
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            | 0.6729        | 5.0   | 15370 | 0.4341          | 0.8169 | 0.8176    | 0.8163 |
         
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            ### Framework versions
         
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        all_results.json
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                "test_runtime": 637.6536,
         
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                "test_samples_per_second": 617.006,
         
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                "test_steps_per_second": 1.206,
         
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                "train_loss": 0. 
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                "train_steps_per_second": 0. 
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            }
         
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                "test_runtime": 637.6536,
         
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                "test_samples_per_second": 617.006,
         
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                "test_steps_per_second": 1.206,
         
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                "train_loss": 0.7952802232433311,
         
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                "train_runtime": 71244.959,
         
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                "train_samples_per_second": 220.891,
         
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                "train_steps_per_second": 0.216
         
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            }
         
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        runs/Jan02_10-47-18_hn-fornix-testing-gpu-platform-2/events.out.tfevents.1735815085.hn-fornix-testing-gpu-platform-2.3915291.0
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        train_results.json
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        trainer_state.json
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