End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+base_model: yihongLiu/furina
+tags:
+- generated_from_trainer
+model-index:
+- name: furina_eng_train_spearman_corr
+  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. -->
+
+# furina_eng_train_spearman_corr
+
+This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0236
+- Spearman Corr: 0.7826
+
+## 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: 32
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
+|:-------------:|:-----:|:----:|:---------------:|:-------------:|
+| 0.0998        | 2.33  | 200  | 0.0146          | 0.7469        |
+| 0.025         | 4.65  | 400  | 0.0226          | 0.7908        |
+| 0.0171        | 6.98  | 600  | 0.0186          | 0.7648        |
+| 0.0136        | 9.3   | 800  | 0.0169          | 0.7634        |
+| 0.0114        | 11.63 | 1000 | 0.0214          | 0.7722        |
+| 0.0081        | 13.95 | 1200 | 0.0221          | 0.7833        |
+| 0.0072        | 16.28 | 1400 | 0.0228          | 0.7853        |
+| 0.0065        | 18.6  | 1600 | 0.0245          | 0.7759        |
+| 0.006         | 20.93 | 1800 | 0.0286          | 0.7788        |
+| 0.0056        | 23.26 | 2000 | 0.0236          | 0.7826        |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.2

config.json

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+  "architectures": [
+    "XLMRobertaForSequenceClassification"
+  ],
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+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
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+  "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": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 401145
+}

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special_tokens_map.json

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tokenizer_config.json

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