End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+model-index:
+- name: ielts-task1-grader-ai-v2
+  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. -->
+
+# ielts-task1-grader-ai-v2
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5069
+- Avg Rmse: 0.7110
+- Rmse Task Response: 0.6879
+- Rmse Coherence Cohesion: 0.6821
+- Rmse Lexical Resource: 0.7008
+- Rmse Grammatical Range: 0.7734
+- Mae Task Response: 0.5352
+- Mae Coherence Cohesion: 0.5415
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Avg Rmse | Rmse Task Response | Rmse Coherence Cohesion | Rmse Lexical Resource | Rmse Grammatical Range | Mae Task Response | Mae Coherence Cohesion |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------------------:|:-----------------------:|:---------------------:|:----------------------:|:-----------------:|:----------------------:|
+| 0.646         | 1.0   | 1567 | 0.5069          | 0.7110   | 0.6879             | 0.6821                  | 0.7008                | 0.7734                 | 0.5352            | 0.5415                 |
+| 0.4782        | 2.0   | 3134 | 0.6015          | 0.7742   | 0.7141             | 0.7474                  | 0.8013                | 0.8339                 | 0.5358            | 0.5963                 |
+| 0.3723        | 3.0   | 4701 | 0.5405          | 0.7339   | 0.6873             | 0.7101                  | 0.7358                | 0.8025                 | 0.5101            | 0.5491                 |
+
+
+### Framework versions
+
+- Transformers 4.57.2
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "transformers_version": "4.57.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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special_tokens_map.json

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+{
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+  "cls_token": "<s>",
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+  "mask_token": {
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+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}

training_args.bin

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