Model save

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+model-index:
+- name: lex-cross-encoder-mbert-10neg
+  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. -->
+
+# lex-cross-encoder-mbert-10neg
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4360
+- Precision: 0.6020
+- Recall: 0.8593
+- F2: 0.7917
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 128
+- total_eval_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F2     |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
+| 0.4572        | 1.0   | 2317  | 0.4705          | 0.4735    | 0.8620 | 0.7405 |
+| 0.4283        | 2.0   | 4634  | 0.4515          | 0.4774    | 0.9124 | 0.7718 |
+| 0.4115        | 3.0   | 6951  | 0.4485          | 0.4796    | 0.9201 | 0.7773 |
+| 0.4021        | 4.0   | 9268  | 0.4387          | 0.5217    | 0.9068 | 0.7902 |
+| 0.3918        | 5.0   | 11585 | 0.4466          | 0.6111    | 0.8242 | 0.7705 |
+| 0.3879        | 6.0   | 13902 | 0.4337          | 0.5783    | 0.8767 | 0.7947 |
+| 0.383         | 7.0   | 16219 | 0.4336          | 0.5633    | 0.8907 | 0.7980 |
+| 0.3781        | 8.0   | 18536 | 0.4354          | 0.5929    | 0.8660 | 0.7930 |
+| 0.3767        | 9.0   | 20853 | 0.4353          | 0.5980    | 0.8636 | 0.7931 |
+| 0.3712        | 10.0  | 23170 | 0.4360          | 0.6020    | 0.8593 | 0.7917 |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.6.0
+- Tokenizers 0.15.2

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