Initial Commit

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- indolem_sentiment
+model-index:
+- name: scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base
+  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. -->
+
+# scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the indolem_sentiment dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6171
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 0.22  | 100  | 0.6046          |
+| No log        | 0.44  | 200  | 0.6079          |
+| No log        | 0.66  | 300  | 0.6091          |
+| No log        | 0.88  | 400  | 0.6057          |
+| 0.6278        | 1.1   | 500  | 0.6073          |
+| 0.6278        | 1.32  | 600  | 0.6139          |
+| 0.6278        | 1.54  | 700  | 0.6050          |
+| 0.6278        | 1.76  | 800  | 0.6120          |
+| 0.6278        | 1.98  | 900  | 0.6073          |
+| 0.6138        | 2.2   | 1000 | 0.6066          |
+| 0.6138        | 2.42  | 1100 | 0.6171          |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.0.1
+- Datasets 2.14.5
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.33.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

pytorch_model.bin

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training_args.bin

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