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xlm-roberta-base-finetuned-panx-de

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xlm-roberta
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Training completed!

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Files changed (10) hide show
  1. README.md +9 -9
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Apr17_18-34-25_YOUNGKIM-PC2/events.out.tfevents.1713346566.YOUNGKIM-PC2.9016.0 +3 -0
  5. runs/Apr17_18-54-20_YOUNGKIM-PC2/events.out.tfevents.1713347775.YOUNGKIM-PC2.22560.0 +3 -0
  6. runs/Apr17_18-58-54_YOUNGKIM-PC2/events.out.tfevents.1713347979.YOUNGKIM-PC2.24968.0 +3 -0
  7. runs/Apr17_19-10-44_YOUNGKIM-PC2/events.out.tfevents.1713348707.YOUNGKIM-PC2.24076.0 +3 -0
  8. runs/Apr17_19-26-42_YOUNGKIM-PC2/events.out.tfevents.1713349656.YOUNGKIM-PC2.24180.0 +3 -0
  9. tokenizer.json +2 -2
  10. training_args.bin +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.1363
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- - F1: 0.8658
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  ## Model description
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@@ -38,8 +38,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 24
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- - eval_batch_size: 24
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -49,14 +49,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.2539 | 1.0 | 525 | 0.1505 | 0.8246 |
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- | 0.1268 | 2.0 | 1050 | 0.1380 | 0.8503 |
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- | 0.0794 | 3.0 | 1575 | 0.1363 | 0.8658 |
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  ### Framework versions
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.1542
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+ - F1: 0.8694
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.2596 | 1.0 | 1573 | 0.1875 | 0.8086 |
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+ | 0.1373 | 2.0 | 3146 | 0.1653 | 0.8513 |
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+ | 0.0806 | 3.0 | 4719 | 0.1542 | 0.8694 |
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  ### Framework versions
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.2+cu118
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -39,7 +39,7 @@
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  "pad_token_id": 1,
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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- "transformers_version": "4.38.2",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 250002
 
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  "pad_token_id": 1,
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.39.3",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 250002
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