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 +1,74 @@
+---
+base_model: yihongLiu/furina
+tags:
+- generated_from_trainer
+model-index:
+- name: furina_seed42_eng_kin_hau_basic_2e-05
+  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_seed42_eng_kin_hau_basic_2e-05
+
+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: 0.0261
+- Spearman Corr: 0.7485
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:-------------:|
+| No log        | 1.59  | 200  | 0.0355          | 0.6099        |
+| 0.0837        | 3.19  | 400  | 0.0284          | 0.7050        |
+| 0.0265        | 4.78  | 600  | 0.0265          | 0.7290        |
+| 0.0202        | 6.37  | 800  | 0.0257          | 0.7317        |
+| 0.0153        | 7.97  | 1000 | 0.0252          | 0.7333        |
+| 0.0153        | 9.56  | 1200 | 0.0254          | 0.7464        |
+| 0.0126        | 11.16 | 1400 | 0.0243          | 0.7483        |
+| 0.0109        | 12.75 | 1600 | 0.0254          | 0.7467        |
+| 0.009         | 14.34 | 1800 | 0.0253          | 0.7463        |
+| 0.0081        | 15.94 | 2000 | 0.0259          | 0.7450        |
+| 0.0081        | 17.53 | 2200 | 0.0258          | 0.7454        |
+| 0.0072        | 19.12 | 2400 | 0.0249          | 0.7474        |
+| 0.0066        | 20.72 | 2600 | 0.0264          | 0.7453        |
+| 0.0061        | 22.31 | 2800 | 0.0252          | 0.7463        |
+| 0.0057        | 23.9  | 3000 | 0.0261          | 0.7485        |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "yihongLiu/furina",
+  "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,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
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+  },
+  "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": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 401145
+}

model.safetensors

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sentencepiece.bpe.model

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special_tokens_map.json

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+}

tokenizer.json

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tokenizer_config.json

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+  "sp_model_kwargs": {},
+  "tokenizer_class": "XLMRobertaTokenizer",
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+  "use_fast": true
+}

training_args.bin

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