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@@ -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 +1,60 @@
+---
+library_name: transformers
+base_model: agentlans/multilingual-e5-small-aligned
+tags:
+- generated_from_trainer
+model-index:
+- name: multilingual-e5-small-aligned-quality
+  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. -->
+
+# multilingual-e5-small-aligned-quality
+
+This model is a fine-tuned version of [agentlans/multilingual-e5-small-aligned](https://huggingface.co/agentlans/multilingual-e5-small-aligned) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2512
+- Mse: 0.2512
+
+## 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: 64
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Mse    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 0.283         | 1.0   | 13548 | 0.2798          | 0.2798 |
+| 0.2212        | 2.0   | 27096 | 0.2522          | 0.2522 |
+| 0.1801        | 3.0   | 40644 | 0.2512          | 0.2512 |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3

all_results.json

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+}

config.json

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+  "architectures": [
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+  ],
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+  "finetuning_task": "text-classification",
+  "hidden_act": "gelu",
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+  "model_type": "bert",
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+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 250037
+}

eval_results.json

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+}

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sentence_bert_config.json

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train_results.json

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