End of training

README.md

@@ -1,6 +1,6 @@
 ---
 library_name: transformers
-license: cc-by-4.0
+license: mit
 base_model: roberta-base
 tags:
 - generated_from_trainer
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5175
-- Accuracy: 0.8230
+- Loss: 0.5008
+- Accuracy: 0.8319
 
 ## Model description
 
@@ -39,22 +39,23 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- num_epochs: 5
+- num_epochs: 6
 
 ### Training results
 
-| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
-|:-------------:|:-----:|:------:|:---------------:|:--------:|
-| 0.5379        | 1.0   | 29470  | 0.6573          | 0.7358   |
-| 0.5714        | 2.0   | 58940  | 0.5810          | 0.7710   |
-| 0.4636        | 3.0   | 88410  | 0.5412          | 0.7918   |
-| 0.4738        | 4.0   | 117880 | 0.5098          | 0.8131   |
-| 0.2801        | 5.0   | 147350 | 0.5175          | 0.8230   |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.6757        | 1.0   | 14844 | 0.6233          | 0.7403   |
+| 0.5788        | 2.0   | 29688 | 0.5779          | 0.7662   |
+| 0.4837        | 3.0   | 44532 | 0.5358          | 0.7866   |
+| 0.5331        | 4.0   | 59376 | 0.4985          | 0.8092   |
+| 0.3582        | 5.0   | 74220 | 0.4885          | 0.8257   |
+| 0.3038        | 6.0   | 89064 | 0.5008          | 0.8319   |
 
 
 ### Framework versions

emissions.csv

@@ -1,2 +1,2 @@
 timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-12-10T14:27:27,codecarbon,bebf79df-4daf-4c49-86c1-c1f4e406acd9,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,17838.959355348954,0.7474642940751101,4.190066691591992e-05,42.5,469.2600301426673,755.7507977485657,0.21042041378611692,3.1492306418824896,3.741270389427118,7.100921445095713,Luxembourg,LUX,,,,Linux-6.8.0-88-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,224,Intel(R) Xeon(R) Platinum 8480+,2,2 x NVIDIA H100 NVL,6.1661,49.7498,2015.3354606628418,machine,N,1.0
+2025-12-15T11:34:11,codecarbon,90df3613-3011-4a1a-a356-4bdeebabc187,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,17918.7004566479,0.7681369216126306,4.286789231568683e-05,42.5,213.13512198891044,755.7507977485657,0.21137087100180996,3.3277749330511597,3.7581658972345817,7.2973117012875415,Luxembourg,LUX,,,,Linux-6.8.0-88-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,224,Intel(R) Xeon(R) Platinum 8480+,2,2 x NVIDIA H100 NVL,6.1661,49.7498,2015.3354606628418,machine,N,1.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:042098df2a6df0230262dbd239961ceb80cbb36877c0ee49d40fd404492e2f81
 size 498618976