Initial Commit

README.md

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+---
+license: mit
+base_model: haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base
+tags:
+- generated_from_trainer
+datasets:
+- indolem_sentiment
+metrics:
+- accuracy
+- f1
+model-index:
+- name: scenario-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained
+  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-kd_weight_copy-data-indolem_sentiment-model-xlmr_base_trained
+
+This model is a fine-tuned version of [haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base](https://huggingface.co/haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base) on the indolem_sentiment dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.8332
+- Accuracy: 0.8471
+- F1: 0.7336
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6969
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 0.88  | 100  | 7.3908          | 0.7419   | 0.6601 |
+| No log        | 1.75  | 200  | 3.5626          | 0.8571   | 0.7816 |
+| No log        | 2.63  | 300  | 8.7677          | 0.7218   | 0.6706 |
+| No log        | 3.51  | 400  | 4.4989          | 0.8346   | 0.7402 |
+| 3.8583        | 4.39  | 500  | 4.6632          | 0.8271   | 0.7273 |
+| 3.8583        | 5.26  | 600  | 4.5488          | 0.8496   | 0.7619 |
+| 3.8583        | 6.14  | 700  | 4.0955          | 0.8697   | 0.7759 |
+| 3.8583        | 7.02  | 800  | 4.4503          | 0.8471   | 0.7404 |
+| 3.8583        | 7.89  | 900  | 4.7169          | 0.8346   | 0.7556 |
+| 1.2007        | 8.77  | 1000 | 3.8991          | 0.8697   | 0.7739 |
+| 1.2007        | 9.65  | 1100 | 5.7272          | 0.8321   | 0.6794 |
+| 1.2007        | 10.53 | 1200 | 4.7281          | 0.8596   | 0.7647 |
+| 1.2007        | 11.4  | 1300 | 8.4804          | 0.8095   | 0.5682 |
+| 1.2007        | 12.28 | 1400 | 4.2305          | 0.8546   | 0.7411 |
+| 0.7006        | 13.16 | 1500 | 4.7921          | 0.8371   | 0.7137 |
+| 0.7006        | 14.04 | 1600 | 4.6111          | 0.8471   | 0.7215 |
+| 0.7006        | 14.91 | 1700 | 4.8332          | 0.8471   | 0.7336 |
+
+
+### 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": "haryoaw/scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForSequenceClassificationKD"
+  ],
+  "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": 6,
+  "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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