Model save

README.md

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----
-license: apache-2.0
----
+---
+library_name: transformers
+license: apache-2.0
+base_model: answerdotai/ModernBERT-large
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: modernBERT-large-multilingual-sentiment
+  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. -->
+
+# modernBERT-large-multilingual-sentiment
+
+This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7490
+- F1: 0.8012
+- Precision: 0.8011
+- Recall: 0.8014
+
+## 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: 512
+- eval_batch_size: 512
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2048
+- total_eval_batch_size: 1024
+- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 5.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
+| 0.8799        | 1.0   | 1537 | 0.4329          | 0.8050 | 0.8079    | 0.8037 |
+| 0.7674        | 2.0   | 3074 | 0.4197          | 0.8125 | 0.8125    | 0.8125 |
+| 0.6427        | 3.0   | 4611 | 0.4399          | 0.8128 | 0.8125    | 0.8133 |
+| 0.4206        | 4.0   | 6148 | 0.5581          | 0.8073 | 0.8068    | 0.8078 |
+| 0.2322        | 5.0   | 7685 | 0.7490          | 0.8012 | 0.8011    | 0.8014 |
+
+
+### Framework versions
+
+- Transformers 4.48.0.dev0
+- Pytorch 2.4.0+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

all_results.json

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+{
+    "epoch": 5.0,
+    "train_loss": 0.6255086388770993,
+    "train_runtime": 65052.9958,
+    "train_samples_per_second": 241.916,
+    "train_steps_per_second": 0.118
+}

model.safetensors

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runs/Jan01_01-06-27_hn-fornix-testing-gpu-platform-2/events.out.tfevents.1735694042.hn-fornix-testing-gpu-platform-2.1051424.0

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train_results.json

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+{
+    "epoch": 5.0,
+    "train_loss": 0.6255086388770993,
+    "train_runtime": 65052.9958,
+    "train_samples_per_second": 241.916,
+    "train_steps_per_second": 0.118
+}