End of training

README.md

@@ -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: 0.5006
-- Accuracy: 0.8308
+- Loss: 0.5008
+- Accuracy: 0.8272
 
 ## Model description
 
@@ -50,16 +50,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step   | Validation Loss | Accuracy |
 |:-------------:|:-----:|:------:|:---------------:|:--------:|
-| 0.6907        | 1.0   | 26806  | 0.6340          | 0.7465   |
-| 0.5341        | 2.0   | 53612  | 0.5606          | 0.7783   |
-| 0.4568        | 3.0   | 80418  | 0.5162          | 0.8029   |
-| 0.437         | 4.0   | 107224 | 0.5003          | 0.8204   |
-| 0.338         | 5.0   | 134030 | 0.5006          | 0.8308   |
+| 0.7147        | 1.0   | 26851  | 0.6525          | 0.7324   |
+| 0.5133        | 2.0   | 53702  | 0.5803          | 0.7693   |
+| 0.4534        | 3.0   | 80553  | 0.5314          | 0.7969   |
+| 0.3721        | 4.0   | 107404 | 0.5030          | 0.8183   |
+| 0.2978        | 5.0   | 134255 | 0.5008          | 0.8272   |
 
 
 ### Framework versions
 
-- Transformers 4.49.0
-- Pytorch 2.6.0+cu124
-- Datasets 3.4.0
+- Transformers 4.51.3
+- Pytorch 2.7.0+cu126
+- Datasets 3.5.0
 - Tokenizers 0.21.1

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
-2025-04-24T17:50:45,codecarbon,d248c2a9-dc29-49db-8bbf-9174c4818b38,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,22025.923609932885,0.3948230483918265,1.7925379901607204e-05,42.5,183.7675567277129,94.34470081329346,0.25984539876734164,2.9141783866185733,0.5768008005733226,3.7508245859592306,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-48-generic-x86_64-with-glibc2.39,3.12.3,2.8.3,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58586883544922,machine,N,1.0
+2025-04-28T13:40:46,codecarbon,c715ed1f-a988-4f23-a458-9522ca614c8a,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,22246.894596571103,0.39704568373654014,1.784724074692818e-05,42.5,175.54676399984314,94.34470081329346,0.2624518737546004,2.926899614017856,0.5825881656341594,3.771939653406611,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-48-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58586883544922,machine,N,1.0