rumodernbert_small_distill

This model is a fine-tuned version of deepvk/RuModernBERT-small on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
lr_scheduler_warmup_steps: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall
4.8701	0.32	200	2.0232	0.4841	0.4288	0.5558
2.6246	0.64	400	1.0239	0.6799	0.6425	0.7219
2.0708	0.96	600	0.9332	0.7623	0.7271	0.8010
1.5292	1.28	800	0.7393	0.7809	0.7670	0.7953
1.1811	1.6	1000	0.6396	0.8126	0.8101	0.8150
1.2625	1.92	1200	0.6523	0.8085	0.7990	0.8182
0.8249	2.24	1400	0.5636	0.8322	0.8294	0.8351
0.8175	2.56	1600	0.5814	0.8361	0.8258	0.8467
0.7697	2.88	1800	0.5125	0.8446	0.8333	0.8563
0.5251	3.2	2000	0.5297	0.8374	0.8268	0.8483
0.5485	3.52	2200	0.4821	0.8542	0.8513	0.8571
0.5174	3.84	2400	0.4683	0.8614	0.8549	0.8680
0.4142	4.16	2600	0.4663	0.8614	0.8564	0.8664
0.3958	4.48	2800	0.4507	0.8622	0.8560	0.8684
0.4127	4.8	3000	0.4406	0.8576	0.8490	0.8664
0.2867	5.12	3200	0.4370	0.8677	0.8592	0.8764
0.3076	5.44	3400	0.4394	0.8612	0.8502	0.8724
0.2746	5.76	3600	0.4325	0.8664	0.8624	0.8704
0.2701	6.08	3800	0.4484	0.8670	0.8632	0.8708