Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: roberta-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. -->
+
+# roberta-large-multilingual-sentiment
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4302
+- F1: 0.8242
+- Precision: 0.8247
+- Recall: 0.8238
+
+## 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
+- gradient_accumulation_steps: 2
+- total_train_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 |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
+| 0.8677        | 1.0   | 3074  | 0.4160          | 0.8113 | 0.8161    | 0.8094 |
+| 0.7994        | 2.0   | 6148  | 0.4053          | 0.8204 | 0.8203    | 0.8207 |
+| 0.687         | 3.0   | 9222  | 0.4036          | 0.8241 | 0.8249    | 0.8235 |
+| 0.6777        | 4.0   | 12296 | 0.4136          | 0.8249 | 0.8256    | 0.8243 |
+| 0.5905        | 5.0   | 15370 | 0.4302          | 0.8242 | 0.8247    | 0.8238 |
+
+
+### 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": 0.7460857761162166,
+    "train_runtime": 176390.3873,
+    "train_samples_per_second": 89.219,
+    "train_steps_per_second": 0.087
+}

model.safetensors

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runs/Jan03_07-02-47_hn-fornix-testing-gpu-platform-2/events.out.tfevents.1735888019.hn-fornix-testing-gpu-platform-2.4140080.0

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train_results.json

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+{
+    "epoch": 5.0,
+    "train_loss": 0.7460857761162166,
+    "train_runtime": 176390.3873,
+    "train_samples_per_second": 89.219,
+    "train_steps_per_second": 0.087
+}