Farouk commited on
Commit
fc2f5eb
·
1 Parent(s): f0a3dd2

Training in progress, step 9000

Browse files
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ea48cfdd90543a9e879837a8bf4a71ccbe3f648fcf1a75dc5c986e6321f3012a
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f857cb43eef3e08e70292b008ae5fdd5dd5108c9047b806632c6b643ae0ba789
3
  size 319977229
checkpoint-3200/adapter_model/adapter_model/README.md CHANGED
@@ -301,6 +301,17 @@ The following `bitsandbytes` quantization config was used during training:
301
  - bnb_4bit_use_double_quant: True
302
  - bnb_4bit_compute_dtype: bfloat16
303
 
 
 
 
 
 
 
 
 
 
 
 
304
  The following `bitsandbytes` quantization config was used during training:
305
  - load_in_8bit: False
306
  - load_in_4bit: True
@@ -340,5 +351,6 @@ The following `bitsandbytes` quantization config was used during training:
340
  - PEFT 0.4.0
341
  - PEFT 0.4.0
342
  - PEFT 0.4.0
 
343
 
344
  - PEFT 0.4.0
 
301
  - bnb_4bit_use_double_quant: True
302
  - bnb_4bit_compute_dtype: bfloat16
303
 
304
+ The following `bitsandbytes` quantization config was used during training:
305
+ - load_in_8bit: False
306
+ - load_in_4bit: True
307
+ - llm_int8_threshold: 6.0
308
+ - llm_int8_skip_modules: None
309
+ - llm_int8_enable_fp32_cpu_offload: False
310
+ - llm_int8_has_fp16_weight: False
311
+ - bnb_4bit_quant_type: nf4
312
+ - bnb_4bit_use_double_quant: True
313
+ - bnb_4bit_compute_dtype: bfloat16
314
+
315
  The following `bitsandbytes` quantization config was used during training:
316
  - load_in_8bit: False
317
  - load_in_4bit: True
 
351
  - PEFT 0.4.0
352
  - PEFT 0.4.0
353
  - PEFT 0.4.0
354
+ - PEFT 0.4.0
355
 
356
  - PEFT 0.4.0
checkpoint-3200/adapter_model/adapter_model/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:88cd97f40aef03dc0ed9614a525e8f808040fcaa895cce579b4864eb9e611a3d
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ea48cfdd90543a9e879837a8bf4a71ccbe3f648fcf1a75dc5c986e6321f3012a
3
  size 319977229
{checkpoint-7000 → checkpoint-9000}/README.md RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/adapter_config.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/adapter_model.bin RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f58c8e6eadf1557ca048de5b9adb0c77d062382bb690dccd8f236969bdafabc1
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f857cb43eef3e08e70292b008ae5fdd5dd5108c9047b806632c6b643ae0ba789
3
  size 319977229
{checkpoint-7000 → checkpoint-9000}/added_tokens.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/optimizer.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:96f16ce85ece583ecbbebfea6040c1a57e20d5c5301c2c4753c45611ce9e022b
3
  size 1279539973
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b16c676365bcbabd67616f251c3ae371fbfd94fae874406a8107467480bd6d8a
3
  size 1279539973
{checkpoint-7000 → checkpoint-9000}/rng_state.pth RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a459b6c31683a6eb7683360095103a6a14bd3984285485ca7b33e7b2aa27018f
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:54d1407ccbce60734442d35e135db002c1e54fc702f1df5db3c4792d0ba01954
3
  size 14511
{checkpoint-7000 → checkpoint-9000}/scheduler.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:47d966fd7801078b5a9187903dada1d3a439c6faaa2aacf8cb8a8b720458f099
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:793b75690a078948aa0821d4f233f78635877d1537467bc47b716dad80584fc5
3
  size 627
{checkpoint-7000 → checkpoint-9000}/special_tokens_map.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/tokenizer.model RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/tokenizer_config.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9000}/trainer_state.json RENAMED
@@ -1,8 +1,8 @@
1
  {
2
  "best_metric": 0.8942907452583313,
3
  "best_model_checkpoint": "experts/expert-31/checkpoint-3200",
4
- "epoch": 2.159827213822894,
5
- "global_step": 7000,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
@@ -6691,11 +6691,1921 @@
6691
  "mmlu_eval_accuracy_world_religions": 0.5789473684210527,
6692
  "mmlu_loss": 1.8355655306001868,
6693
  "step": 7000
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6694
  }
6695
  ],
6696
  "max_steps": 10000,
6697
  "num_train_epochs": 4,
6698
- "total_flos": 3.850371817739059e+17,
6699
  "trial_name": null,
6700
  "trial_params": null
6701
  }
 
1
  {
2
  "best_metric": 0.8942907452583313,
3
  "best_model_checkpoint": "experts/expert-31/checkpoint-3200",
4
+ "epoch": 2.7769207034865784,
5
+ "global_step": 9000,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
 
6691
  "mmlu_eval_accuracy_world_religions": 0.5789473684210527,
6692
  "mmlu_loss": 1.8355655306001868,
6693
  "step": 7000
6694
+ },
6695
+ {
6696
+ "epoch": 2.16,
6697
+ "learning_rate": 0.0002,
6698
+ "loss": 0.7195,
6699
+ "step": 7010
6700
+ },
6701
+ {
6702
+ "epoch": 2.17,
6703
+ "learning_rate": 0.0002,
6704
+ "loss": 0.7495,
6705
+ "step": 7020
6706
+ },
6707
+ {
6708
+ "epoch": 2.17,
6709
+ "learning_rate": 0.0002,
6710
+ "loss": 0.7932,
6711
+ "step": 7030
6712
+ },
6713
+ {
6714
+ "epoch": 2.17,
6715
+ "learning_rate": 0.0002,
6716
+ "loss": 0.7808,
6717
+ "step": 7040
6718
+ },
6719
+ {
6720
+ "epoch": 2.18,
6721
+ "learning_rate": 0.0002,
6722
+ "loss": 0.7049,
6723
+ "step": 7050
6724
+ },
6725
+ {
6726
+ "epoch": 2.18,
6727
+ "learning_rate": 0.0002,
6728
+ "loss": 0.7224,
6729
+ "step": 7060
6730
+ },
6731
+ {
6732
+ "epoch": 2.18,
6733
+ "learning_rate": 0.0002,
6734
+ "loss": 0.7119,
6735
+ "step": 7070
6736
+ },
6737
+ {
6738
+ "epoch": 2.18,
6739
+ "learning_rate": 0.0002,
6740
+ "loss": 0.7113,
6741
+ "step": 7080
6742
+ },
6743
+ {
6744
+ "epoch": 2.19,
6745
+ "learning_rate": 0.0002,
6746
+ "loss": 0.7803,
6747
+ "step": 7090
6748
+ },
6749
+ {
6750
+ "epoch": 2.19,
6751
+ "learning_rate": 0.0002,
6752
+ "loss": 0.7544,
6753
+ "step": 7100
6754
+ },
6755
+ {
6756
+ "epoch": 2.19,
6757
+ "learning_rate": 0.0002,
6758
+ "loss": 0.7502,
6759
+ "step": 7110
6760
+ },
6761
+ {
6762
+ "epoch": 2.2,
6763
+ "learning_rate": 0.0002,
6764
+ "loss": 0.7637,
6765
+ "step": 7120
6766
+ },
6767
+ {
6768
+ "epoch": 2.2,
6769
+ "learning_rate": 0.0002,
6770
+ "loss": 0.7091,
6771
+ "step": 7130
6772
+ },
6773
+ {
6774
+ "epoch": 2.2,
6775
+ "learning_rate": 0.0002,
6776
+ "loss": 0.7605,
6777
+ "step": 7140
6778
+ },
6779
+ {
6780
+ "epoch": 2.21,
6781
+ "learning_rate": 0.0002,
6782
+ "loss": 0.7067,
6783
+ "step": 7150
6784
+ },
6785
+ {
6786
+ "epoch": 2.21,
6787
+ "learning_rate": 0.0002,
6788
+ "loss": 0.7595,
6789
+ "step": 7160
6790
+ },
6791
+ {
6792
+ "epoch": 2.21,
6793
+ "learning_rate": 0.0002,
6794
+ "loss": 0.7491,
6795
+ "step": 7170
6796
+ },
6797
+ {
6798
+ "epoch": 2.22,
6799
+ "learning_rate": 0.0002,
6800
+ "loss": 0.7933,
6801
+ "step": 7180
6802
+ },
6803
+ {
6804
+ "epoch": 2.22,
6805
+ "learning_rate": 0.0002,
6806
+ "loss": 0.7521,
6807
+ "step": 7190
6808
+ },
6809
+ {
6810
+ "epoch": 2.22,
6811
+ "learning_rate": 0.0002,
6812
+ "loss": 0.7176,
6813
+ "step": 7200
6814
+ },
6815
+ {
6816
+ "epoch": 2.22,
6817
+ "eval_loss": 0.9252617359161377,
6818
+ "eval_runtime": 85.7177,
6819
+ "eval_samples_per_second": 11.666,
6820
+ "eval_steps_per_second": 5.833,
6821
+ "step": 7200
6822
+ },
6823
+ {
6824
+ "epoch": 2.22,
6825
+ "mmlu_eval_accuracy": 0.37470774879895086,
6826
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
6827
+ "mmlu_eval_accuracy_anatomy": 0.5,
6828
+ "mmlu_eval_accuracy_astronomy": 0.25,
6829
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
6830
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
6831
+ "mmlu_eval_accuracy_college_biology": 0.5,
6832
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
6833
+ "mmlu_eval_accuracy_college_computer_science": 0.18181818181818182,
6834
+ "mmlu_eval_accuracy_college_mathematics": 0.09090909090909091,
6835
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
6836
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
6837
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
6838
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
6839
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
6840
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
6841
+ "mmlu_eval_accuracy_elementary_mathematics": 0.1951219512195122,
6842
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
6843
+ "mmlu_eval_accuracy_global_facts": 0.2,
6844
+ "mmlu_eval_accuracy_high_school_biology": 0.34375,
6845
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
6846
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6847
+ "mmlu_eval_accuracy_high_school_european_history": 0.5,
6848
+ "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
6849
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
6850
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
6851
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
6852
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
6853
+ "mmlu_eval_accuracy_high_school_physics": 0.058823529411764705,
6854
+ "mmlu_eval_accuracy_high_school_psychology": 0.5,
6855
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
6856
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
6857
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
6858
+ "mmlu_eval_accuracy_human_aging": 0.43478260869565216,
6859
+ "mmlu_eval_accuracy_human_sexuality": 0.16666666666666666,
6860
+ "mmlu_eval_accuracy_international_law": 0.6923076923076923,
6861
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
6862
+ "mmlu_eval_accuracy_logical_fallacies": 0.3333333333333333,
6863
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
6864
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
6865
+ "mmlu_eval_accuracy_marketing": 0.8,
6866
+ "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364,
6867
+ "mmlu_eval_accuracy_miscellaneous": 0.5,
6868
+ "mmlu_eval_accuracy_moral_disputes": 0.3684210526315789,
6869
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
6870
+ "mmlu_eval_accuracy_nutrition": 0.42424242424242425,
6871
+ "mmlu_eval_accuracy_philosophy": 0.2647058823529412,
6872
+ "mmlu_eval_accuracy_prehistory": 0.34285714285714286,
6873
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
6874
+ "mmlu_eval_accuracy_professional_law": 0.3176470588235294,
6875
+ "mmlu_eval_accuracy_professional_medicine": 0.25806451612903225,
6876
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
6877
+ "mmlu_eval_accuracy_public_relations": 0.5,
6878
+ "mmlu_eval_accuracy_security_studies": 0.37037037037037035,
6879
+ "mmlu_eval_accuracy_sociology": 0.5,
6880
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
6881
+ "mmlu_eval_accuracy_virology": 0.3888888888888889,
6882
+ "mmlu_eval_accuracy_world_religions": 0.5263157894736842,
6883
+ "mmlu_loss": 1.7208241467843168,
6884
+ "step": 7200
6885
+ },
6886
+ {
6887
+ "epoch": 2.22,
6888
+ "learning_rate": 0.0002,
6889
+ "loss": 0.7271,
6890
+ "step": 7210
6891
+ },
6892
+ {
6893
+ "epoch": 2.23,
6894
+ "learning_rate": 0.0002,
6895
+ "loss": 0.7088,
6896
+ "step": 7220
6897
+ },
6898
+ {
6899
+ "epoch": 2.23,
6900
+ "learning_rate": 0.0002,
6901
+ "loss": 0.7611,
6902
+ "step": 7230
6903
+ },
6904
+ {
6905
+ "epoch": 2.23,
6906
+ "learning_rate": 0.0002,
6907
+ "loss": 0.7355,
6908
+ "step": 7240
6909
+ },
6910
+ {
6911
+ "epoch": 2.24,
6912
+ "learning_rate": 0.0002,
6913
+ "loss": 0.7485,
6914
+ "step": 7250
6915
+ },
6916
+ {
6917
+ "epoch": 2.24,
6918
+ "learning_rate": 0.0002,
6919
+ "loss": 0.7318,
6920
+ "step": 7260
6921
+ },
6922
+ {
6923
+ "epoch": 2.24,
6924
+ "learning_rate": 0.0002,
6925
+ "loss": 0.79,
6926
+ "step": 7270
6927
+ },
6928
+ {
6929
+ "epoch": 2.25,
6930
+ "learning_rate": 0.0002,
6931
+ "loss": 0.807,
6932
+ "step": 7280
6933
+ },
6934
+ {
6935
+ "epoch": 2.25,
6936
+ "learning_rate": 0.0002,
6937
+ "loss": 0.7418,
6938
+ "step": 7290
6939
+ },
6940
+ {
6941
+ "epoch": 2.25,
6942
+ "learning_rate": 0.0002,
6943
+ "loss": 0.7172,
6944
+ "step": 7300
6945
+ },
6946
+ {
6947
+ "epoch": 2.26,
6948
+ "learning_rate": 0.0002,
6949
+ "loss": 0.7251,
6950
+ "step": 7310
6951
+ },
6952
+ {
6953
+ "epoch": 2.26,
6954
+ "learning_rate": 0.0002,
6955
+ "loss": 0.7241,
6956
+ "step": 7320
6957
+ },
6958
+ {
6959
+ "epoch": 2.26,
6960
+ "learning_rate": 0.0002,
6961
+ "loss": 0.7803,
6962
+ "step": 7330
6963
+ },
6964
+ {
6965
+ "epoch": 2.26,
6966
+ "learning_rate": 0.0002,
6967
+ "loss": 0.736,
6968
+ "step": 7340
6969
+ },
6970
+ {
6971
+ "epoch": 2.27,
6972
+ "learning_rate": 0.0002,
6973
+ "loss": 0.7434,
6974
+ "step": 7350
6975
+ },
6976
+ {
6977
+ "epoch": 2.27,
6978
+ "learning_rate": 0.0002,
6979
+ "loss": 0.7735,
6980
+ "step": 7360
6981
+ },
6982
+ {
6983
+ "epoch": 2.27,
6984
+ "learning_rate": 0.0002,
6985
+ "loss": 0.7211,
6986
+ "step": 7370
6987
+ },
6988
+ {
6989
+ "epoch": 2.28,
6990
+ "learning_rate": 0.0002,
6991
+ "loss": 0.7257,
6992
+ "step": 7380
6993
+ },
6994
+ {
6995
+ "epoch": 2.28,
6996
+ "learning_rate": 0.0002,
6997
+ "loss": 0.7179,
6998
+ "step": 7390
6999
+ },
7000
+ {
7001
+ "epoch": 2.28,
7002
+ "learning_rate": 0.0002,
7003
+ "loss": 0.7676,
7004
+ "step": 7400
7005
+ },
7006
+ {
7007
+ "epoch": 2.28,
7008
+ "eval_loss": 0.9213372468948364,
7009
+ "eval_runtime": 85.6714,
7010
+ "eval_samples_per_second": 11.673,
7011
+ "eval_steps_per_second": 5.836,
7012
+ "step": 7400
7013
+ },
7014
+ {
7015
+ "epoch": 2.28,
7016
+ "mmlu_eval_accuracy": 0.38913458140112916,
7017
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7018
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
7019
+ "mmlu_eval_accuracy_astronomy": 0.375,
7020
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7021
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
7022
+ "mmlu_eval_accuracy_college_biology": 0.375,
7023
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7024
+ "mmlu_eval_accuracy_college_computer_science": 0.18181818181818182,
7025
+ "mmlu_eval_accuracy_college_mathematics": 0.09090909090909091,
7026
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
7027
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
7028
+ "mmlu_eval_accuracy_computer_security": 0.18181818181818182,
7029
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
7030
+ "mmlu_eval_accuracy_econometrics": 0.25,
7031
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
7032
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2682926829268293,
7033
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
7034
+ "mmlu_eval_accuracy_global_facts": 0.2,
7035
+ "mmlu_eval_accuracy_high_school_biology": 0.3125,
7036
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
7037
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7038
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
7039
+ "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
7040
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
7041
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
7042
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
7043
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
7044
+ "mmlu_eval_accuracy_high_school_physics": 0.058823529411764705,
7045
+ "mmlu_eval_accuracy_high_school_psychology": 0.5166666666666667,
7046
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
7047
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
7048
+ "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
7049
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
7050
+ "mmlu_eval_accuracy_human_sexuality": 0.16666666666666666,
7051
+ "mmlu_eval_accuracy_international_law": 0.6923076923076923,
7052
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7053
+ "mmlu_eval_accuracy_logical_fallacies": 0.5,
7054
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7055
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
7056
+ "mmlu_eval_accuracy_marketing": 0.84,
7057
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
7058
+ "mmlu_eval_accuracy_miscellaneous": 0.5116279069767442,
7059
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
7060
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
7061
+ "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
7062
+ "mmlu_eval_accuracy_philosophy": 0.3235294117647059,
7063
+ "mmlu_eval_accuracy_prehistory": 0.34285714285714286,
7064
+ "mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
7065
+ "mmlu_eval_accuracy_professional_law": 0.29411764705882354,
7066
+ "mmlu_eval_accuracy_professional_medicine": 0.3225806451612903,
7067
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
7068
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
7069
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7070
+ "mmlu_eval_accuracy_sociology": 0.6363636363636364,
7071
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
7072
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7073
+ "mmlu_eval_accuracy_world_religions": 0.5789473684210527,
7074
+ "mmlu_loss": 1.7146176414919274,
7075
+ "step": 7400
7076
+ },
7077
+ {
7078
+ "epoch": 2.29,
7079
+ "learning_rate": 0.0002,
7080
+ "loss": 0.8092,
7081
+ "step": 7410
7082
+ },
7083
+ {
7084
+ "epoch": 2.29,
7085
+ "learning_rate": 0.0002,
7086
+ "loss": 0.7236,
7087
+ "step": 7420
7088
+ },
7089
+ {
7090
+ "epoch": 2.29,
7091
+ "learning_rate": 0.0002,
7092
+ "loss": 0.712,
7093
+ "step": 7430
7094
+ },
7095
+ {
7096
+ "epoch": 2.3,
7097
+ "learning_rate": 0.0002,
7098
+ "loss": 0.7135,
7099
+ "step": 7440
7100
+ },
7101
+ {
7102
+ "epoch": 2.3,
7103
+ "learning_rate": 0.0002,
7104
+ "loss": 0.7083,
7105
+ "step": 7450
7106
+ },
7107
+ {
7108
+ "epoch": 2.3,
7109
+ "learning_rate": 0.0002,
7110
+ "loss": 0.7572,
7111
+ "step": 7460
7112
+ },
7113
+ {
7114
+ "epoch": 2.3,
7115
+ "learning_rate": 0.0002,
7116
+ "loss": 0.7428,
7117
+ "step": 7470
7118
+ },
7119
+ {
7120
+ "epoch": 2.31,
7121
+ "learning_rate": 0.0002,
7122
+ "loss": 0.7882,
7123
+ "step": 7480
7124
+ },
7125
+ {
7126
+ "epoch": 2.31,
7127
+ "learning_rate": 0.0002,
7128
+ "loss": 0.7717,
7129
+ "step": 7490
7130
+ },
7131
+ {
7132
+ "epoch": 2.31,
7133
+ "learning_rate": 0.0002,
7134
+ "loss": 0.7406,
7135
+ "step": 7500
7136
+ },
7137
+ {
7138
+ "epoch": 2.32,
7139
+ "learning_rate": 0.0002,
7140
+ "loss": 0.8373,
7141
+ "step": 7510
7142
+ },
7143
+ {
7144
+ "epoch": 2.32,
7145
+ "learning_rate": 0.0002,
7146
+ "loss": 0.7069,
7147
+ "step": 7520
7148
+ },
7149
+ {
7150
+ "epoch": 2.32,
7151
+ "learning_rate": 0.0002,
7152
+ "loss": 0.72,
7153
+ "step": 7530
7154
+ },
7155
+ {
7156
+ "epoch": 2.33,
7157
+ "learning_rate": 0.0002,
7158
+ "loss": 0.7356,
7159
+ "step": 7540
7160
+ },
7161
+ {
7162
+ "epoch": 2.33,
7163
+ "learning_rate": 0.0002,
7164
+ "loss": 0.778,
7165
+ "step": 7550
7166
+ },
7167
+ {
7168
+ "epoch": 2.33,
7169
+ "learning_rate": 0.0002,
7170
+ "loss": 0.7451,
7171
+ "step": 7560
7172
+ },
7173
+ {
7174
+ "epoch": 2.34,
7175
+ "learning_rate": 0.0002,
7176
+ "loss": 0.7302,
7177
+ "step": 7570
7178
+ },
7179
+ {
7180
+ "epoch": 2.34,
7181
+ "learning_rate": 0.0002,
7182
+ "loss": 0.8005,
7183
+ "step": 7580
7184
+ },
7185
+ {
7186
+ "epoch": 2.34,
7187
+ "learning_rate": 0.0002,
7188
+ "loss": 0.8012,
7189
+ "step": 7590
7190
+ },
7191
+ {
7192
+ "epoch": 2.34,
7193
+ "learning_rate": 0.0002,
7194
+ "loss": 0.7277,
7195
+ "step": 7600
7196
+ },
7197
+ {
7198
+ "epoch": 2.34,
7199
+ "eval_loss": 0.918026864528656,
7200
+ "eval_runtime": 85.7178,
7201
+ "eval_samples_per_second": 11.666,
7202
+ "eval_steps_per_second": 5.833,
7203
+ "step": 7600
7204
+ },
7205
+ {
7206
+ "epoch": 2.34,
7207
+ "mmlu_eval_accuracy": 0.4047312825854751,
7208
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7209
+ "mmlu_eval_accuracy_anatomy": 0.5,
7210
+ "mmlu_eval_accuracy_astronomy": 0.375,
7211
+ "mmlu_eval_accuracy_business_ethics": 0.36363636363636365,
7212
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
7213
+ "mmlu_eval_accuracy_college_biology": 0.4375,
7214
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7215
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7216
+ "mmlu_eval_accuracy_college_mathematics": 0.09090909090909091,
7217
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
7218
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
7219
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7220
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
7221
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
7222
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
7223
+ "mmlu_eval_accuracy_elementary_mathematics": 0.24390243902439024,
7224
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
7225
+ "mmlu_eval_accuracy_global_facts": 0.2,
7226
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
7227
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
7228
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7229
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
7230
+ "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
7231
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.2857142857142857,
7232
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
7233
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
7234
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.7307692307692307,
7235
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
7236
+ "mmlu_eval_accuracy_high_school_psychology": 0.5833333333333334,
7237
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
7238
+ "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
7239
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
7240
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
7241
+ "mmlu_eval_accuracy_human_sexuality": 0.25,
7242
+ "mmlu_eval_accuracy_international_law": 0.6153846153846154,
7243
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
7244
+ "mmlu_eval_accuracy_logical_fallacies": 0.4444444444444444,
7245
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
7246
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
7247
+ "mmlu_eval_accuracy_marketing": 0.72,
7248
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
7249
+ "mmlu_eval_accuracy_miscellaneous": 0.5116279069767442,
7250
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
7251
+ "mmlu_eval_accuracy_moral_scenarios": 0.27,
7252
+ "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
7253
+ "mmlu_eval_accuracy_philosophy": 0.3235294117647059,
7254
+ "mmlu_eval_accuracy_prehistory": 0.34285714285714286,
7255
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
7256
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
7257
+ "mmlu_eval_accuracy_professional_medicine": 0.3548387096774194,
7258
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
7259
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
7260
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7261
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
7262
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
7263
+ "mmlu_eval_accuracy_virology": 0.3888888888888889,
7264
+ "mmlu_eval_accuracy_world_religions": 0.47368421052631576,
7265
+ "mmlu_loss": 1.7352643367827094,
7266
+ "step": 7600
7267
+ },
7268
+ {
7269
+ "epoch": 2.35,
7270
+ "learning_rate": 0.0002,
7271
+ "loss": 0.7752,
7272
+ "step": 7610
7273
+ },
7274
+ {
7275
+ "epoch": 2.35,
7276
+ "learning_rate": 0.0002,
7277
+ "loss": 0.7836,
7278
+ "step": 7620
7279
+ },
7280
+ {
7281
+ "epoch": 2.35,
7282
+ "learning_rate": 0.0002,
7283
+ "loss": 0.7207,
7284
+ "step": 7630
7285
+ },
7286
+ {
7287
+ "epoch": 2.36,
7288
+ "learning_rate": 0.0002,
7289
+ "loss": 0.7835,
7290
+ "step": 7640
7291
+ },
7292
+ {
7293
+ "epoch": 2.36,
7294
+ "learning_rate": 0.0002,
7295
+ "loss": 0.6881,
7296
+ "step": 7650
7297
+ },
7298
+ {
7299
+ "epoch": 2.36,
7300
+ "learning_rate": 0.0002,
7301
+ "loss": 0.7563,
7302
+ "step": 7660
7303
+ },
7304
+ {
7305
+ "epoch": 2.37,
7306
+ "learning_rate": 0.0002,
7307
+ "loss": 0.7434,
7308
+ "step": 7670
7309
+ },
7310
+ {
7311
+ "epoch": 2.37,
7312
+ "learning_rate": 0.0002,
7313
+ "loss": 0.7337,
7314
+ "step": 7680
7315
+ },
7316
+ {
7317
+ "epoch": 2.37,
7318
+ "learning_rate": 0.0002,
7319
+ "loss": 0.754,
7320
+ "step": 7690
7321
+ },
7322
+ {
7323
+ "epoch": 2.38,
7324
+ "learning_rate": 0.0002,
7325
+ "loss": 0.7604,
7326
+ "step": 7700
7327
+ },
7328
+ {
7329
+ "epoch": 2.38,
7330
+ "learning_rate": 0.0002,
7331
+ "loss": 0.7015,
7332
+ "step": 7710
7333
+ },
7334
+ {
7335
+ "epoch": 2.38,
7336
+ "learning_rate": 0.0002,
7337
+ "loss": 0.7809,
7338
+ "step": 7720
7339
+ },
7340
+ {
7341
+ "epoch": 2.39,
7342
+ "learning_rate": 0.0002,
7343
+ "loss": 0.6738,
7344
+ "step": 7730
7345
+ },
7346
+ {
7347
+ "epoch": 2.39,
7348
+ "learning_rate": 0.0002,
7349
+ "loss": 0.7371,
7350
+ "step": 7740
7351
+ },
7352
+ {
7353
+ "epoch": 2.39,
7354
+ "learning_rate": 0.0002,
7355
+ "loss": 0.7822,
7356
+ "step": 7750
7357
+ },
7358
+ {
7359
+ "epoch": 2.39,
7360
+ "learning_rate": 0.0002,
7361
+ "loss": 0.783,
7362
+ "step": 7760
7363
+ },
7364
+ {
7365
+ "epoch": 2.4,
7366
+ "learning_rate": 0.0002,
7367
+ "loss": 0.7421,
7368
+ "step": 7770
7369
+ },
7370
+ {
7371
+ "epoch": 2.4,
7372
+ "learning_rate": 0.0002,
7373
+ "loss": 0.7224,
7374
+ "step": 7780
7375
+ },
7376
+ {
7377
+ "epoch": 2.4,
7378
+ "learning_rate": 0.0002,
7379
+ "loss": 0.7775,
7380
+ "step": 7790
7381
+ },
7382
+ {
7383
+ "epoch": 2.41,
7384
+ "learning_rate": 0.0002,
7385
+ "loss": 0.7535,
7386
+ "step": 7800
7387
+ },
7388
+ {
7389
+ "epoch": 2.41,
7390
+ "eval_loss": 0.9267637729644775,
7391
+ "eval_runtime": 85.7636,
7392
+ "eval_samples_per_second": 11.66,
7393
+ "eval_steps_per_second": 5.83,
7394
+ "step": 7800
7395
+ },
7396
+ {
7397
+ "epoch": 2.41,
7398
+ "mmlu_eval_accuracy": 0.39241158570203216,
7399
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7400
+ "mmlu_eval_accuracy_anatomy": 0.42857142857142855,
7401
+ "mmlu_eval_accuracy_astronomy": 0.3125,
7402
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7403
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
7404
+ "mmlu_eval_accuracy_college_biology": 0.375,
7405
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7406
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7407
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
7408
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
7409
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7410
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
7411
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
7412
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
7413
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7414
+ "mmlu_eval_accuracy_elementary_mathematics": 0.1951219512195122,
7415
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
7416
+ "mmlu_eval_accuracy_global_facts": 0.2,
7417
+ "mmlu_eval_accuracy_high_school_biology": 0.34375,
7418
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
7419
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7420
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7421
+ "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
7422
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
7423
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
7424
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
7425
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
7426
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7427
+ "mmlu_eval_accuracy_high_school_psychology": 0.5,
7428
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
7429
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
7430
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
7431
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
7432
+ "mmlu_eval_accuracy_human_sexuality": 0.16666666666666666,
7433
+ "mmlu_eval_accuracy_international_law": 0.6923076923076923,
7434
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
7435
+ "mmlu_eval_accuracy_logical_fallacies": 0.5,
7436
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7437
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
7438
+ "mmlu_eval_accuracy_marketing": 0.8,
7439
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
7440
+ "mmlu_eval_accuracy_miscellaneous": 0.5465116279069767,
7441
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
7442
+ "mmlu_eval_accuracy_moral_scenarios": 0.28,
7443
+ "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
7444
+ "mmlu_eval_accuracy_philosophy": 0.3235294117647059,
7445
+ "mmlu_eval_accuracy_prehistory": 0.2857142857142857,
7446
+ "mmlu_eval_accuracy_professional_accounting": 0.41935483870967744,
7447
+ "mmlu_eval_accuracy_professional_law": 0.3,
7448
+ "mmlu_eval_accuracy_professional_medicine": 0.3548387096774194,
7449
+ "mmlu_eval_accuracy_professional_psychology": 0.4492753623188406,
7450
+ "mmlu_eval_accuracy_public_relations": 0.5,
7451
+ "mmlu_eval_accuracy_security_studies": 0.3333333333333333,
7452
+ "mmlu_eval_accuracy_sociology": 0.5,
7453
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
7454
+ "mmlu_eval_accuracy_virology": 0.5,
7455
+ "mmlu_eval_accuracy_world_religions": 0.5263157894736842,
7456
+ "mmlu_loss": 1.900582846088758,
7457
+ "step": 7800
7458
+ },
7459
+ {
7460
+ "epoch": 2.41,
7461
+ "learning_rate": 0.0002,
7462
+ "loss": 0.7305,
7463
+ "step": 7810
7464
+ },
7465
+ {
7466
+ "epoch": 2.41,
7467
+ "learning_rate": 0.0002,
7468
+ "loss": 0.7969,
7469
+ "step": 7820
7470
+ },
7471
+ {
7472
+ "epoch": 2.42,
7473
+ "learning_rate": 0.0002,
7474
+ "loss": 0.7137,
7475
+ "step": 7830
7476
+ },
7477
+ {
7478
+ "epoch": 2.42,
7479
+ "learning_rate": 0.0002,
7480
+ "loss": 0.7612,
7481
+ "step": 7840
7482
+ },
7483
+ {
7484
+ "epoch": 2.42,
7485
+ "learning_rate": 0.0002,
7486
+ "loss": 0.8423,
7487
+ "step": 7850
7488
+ },
7489
+ {
7490
+ "epoch": 2.43,
7491
+ "learning_rate": 0.0002,
7492
+ "loss": 0.7562,
7493
+ "step": 7860
7494
+ },
7495
+ {
7496
+ "epoch": 2.43,
7497
+ "learning_rate": 0.0002,
7498
+ "loss": 0.7151,
7499
+ "step": 7870
7500
+ },
7501
+ {
7502
+ "epoch": 2.43,
7503
+ "learning_rate": 0.0002,
7504
+ "loss": 0.7944,
7505
+ "step": 7880
7506
+ },
7507
+ {
7508
+ "epoch": 2.43,
7509
+ "learning_rate": 0.0002,
7510
+ "loss": 0.7462,
7511
+ "step": 7890
7512
+ },
7513
+ {
7514
+ "epoch": 2.44,
7515
+ "learning_rate": 0.0002,
7516
+ "loss": 0.7935,
7517
+ "step": 7900
7518
+ },
7519
+ {
7520
+ "epoch": 2.44,
7521
+ "learning_rate": 0.0002,
7522
+ "loss": 0.7509,
7523
+ "step": 7910
7524
+ },
7525
+ {
7526
+ "epoch": 2.44,
7527
+ "learning_rate": 0.0002,
7528
+ "loss": 0.7532,
7529
+ "step": 7920
7530
+ },
7531
+ {
7532
+ "epoch": 2.45,
7533
+ "learning_rate": 0.0002,
7534
+ "loss": 0.7464,
7535
+ "step": 7930
7536
+ },
7537
+ {
7538
+ "epoch": 2.45,
7539
+ "learning_rate": 0.0002,
7540
+ "loss": 0.7712,
7541
+ "step": 7940
7542
+ },
7543
+ {
7544
+ "epoch": 2.45,
7545
+ "learning_rate": 0.0002,
7546
+ "loss": 0.7818,
7547
+ "step": 7950
7548
+ },
7549
+ {
7550
+ "epoch": 2.46,
7551
+ "learning_rate": 0.0002,
7552
+ "loss": 0.7819,
7553
+ "step": 7960
7554
+ },
7555
+ {
7556
+ "epoch": 2.46,
7557
+ "learning_rate": 0.0002,
7558
+ "loss": 0.7352,
7559
+ "step": 7970
7560
+ },
7561
+ {
7562
+ "epoch": 2.46,
7563
+ "learning_rate": 0.0002,
7564
+ "loss": 0.7666,
7565
+ "step": 7980
7566
+ },
7567
+ {
7568
+ "epoch": 2.47,
7569
+ "learning_rate": 0.0002,
7570
+ "loss": 0.6924,
7571
+ "step": 7990
7572
+ },
7573
+ {
7574
+ "epoch": 2.47,
7575
+ "learning_rate": 0.0002,
7576
+ "loss": 0.7311,
7577
+ "step": 8000
7578
+ },
7579
+ {
7580
+ "epoch": 2.47,
7581
+ "eval_loss": 0.924709141254425,
7582
+ "eval_runtime": 85.749,
7583
+ "eval_samples_per_second": 11.662,
7584
+ "eval_steps_per_second": 5.831,
7585
+ "step": 8000
7586
+ },
7587
+ {
7588
+ "epoch": 2.47,
7589
+ "mmlu_eval_accuracy": 0.3950240676266018,
7590
+ "mmlu_eval_accuracy_abstract_algebra": 0.09090909090909091,
7591
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7592
+ "mmlu_eval_accuracy_astronomy": 0.25,
7593
+ "mmlu_eval_accuracy_business_ethics": 0.36363636363636365,
7594
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
7595
+ "mmlu_eval_accuracy_college_biology": 0.3125,
7596
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7597
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7598
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
7599
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
7600
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7601
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
7602
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
7603
+ "mmlu_eval_accuracy_econometrics": 0.08333333333333333,
7604
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7605
+ "mmlu_eval_accuracy_elementary_mathematics": 0.1951219512195122,
7606
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
7607
+ "mmlu_eval_accuracy_global_facts": 0.2,
7608
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
7609
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
7610
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7611
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
7612
+ "mmlu_eval_accuracy_high_school_geography": 0.7272727272727273,
7613
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
7614
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
7615
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
7616
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6923076923076923,
7617
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7618
+ "mmlu_eval_accuracy_high_school_psychology": 0.5166666666666667,
7619
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
7620
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
7621
+ "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
7622
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
7623
+ "mmlu_eval_accuracy_human_sexuality": 0.25,
7624
+ "mmlu_eval_accuracy_international_law": 0.6153846153846154,
7625
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
7626
+ "mmlu_eval_accuracy_logical_fallacies": 0.5,
7627
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
7628
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
7629
+ "mmlu_eval_accuracy_marketing": 0.8,
7630
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
7631
+ "mmlu_eval_accuracy_miscellaneous": 0.5232558139534884,
7632
+ "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
7633
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
7634
+ "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
7635
+ "mmlu_eval_accuracy_philosophy": 0.29411764705882354,
7636
+ "mmlu_eval_accuracy_prehistory": 0.34285714285714286,
7637
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
7638
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
7639
+ "mmlu_eval_accuracy_professional_medicine": 0.3225806451612903,
7640
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
7641
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
7642
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7643
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
7644
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
7645
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7646
+ "mmlu_eval_accuracy_world_religions": 0.5789473684210527,
7647
+ "mmlu_loss": 1.7345892876464455,
7648
+ "step": 8000
7649
+ },
7650
+ {
7651
+ "epoch": 2.47,
7652
+ "learning_rate": 0.0002,
7653
+ "loss": 0.7127,
7654
+ "step": 8010
7655
+ },
7656
+ {
7657
+ "epoch": 2.47,
7658
+ "learning_rate": 0.0002,
7659
+ "loss": 0.8475,
7660
+ "step": 8020
7661
+ },
7662
+ {
7663
+ "epoch": 2.48,
7664
+ "learning_rate": 0.0002,
7665
+ "loss": 0.7452,
7666
+ "step": 8030
7667
+ },
7668
+ {
7669
+ "epoch": 2.48,
7670
+ "learning_rate": 0.0002,
7671
+ "loss": 0.7682,
7672
+ "step": 8040
7673
+ },
7674
+ {
7675
+ "epoch": 2.48,
7676
+ "learning_rate": 0.0002,
7677
+ "loss": 0.7533,
7678
+ "step": 8050
7679
+ },
7680
+ {
7681
+ "epoch": 2.49,
7682
+ "learning_rate": 0.0002,
7683
+ "loss": 0.7378,
7684
+ "step": 8060
7685
+ },
7686
+ {
7687
+ "epoch": 2.49,
7688
+ "learning_rate": 0.0002,
7689
+ "loss": 0.8175,
7690
+ "step": 8070
7691
+ },
7692
+ {
7693
+ "epoch": 2.49,
7694
+ "learning_rate": 0.0002,
7695
+ "loss": 0.7294,
7696
+ "step": 8080
7697
+ },
7698
+ {
7699
+ "epoch": 2.5,
7700
+ "learning_rate": 0.0002,
7701
+ "loss": 0.7581,
7702
+ "step": 8090
7703
+ },
7704
+ {
7705
+ "epoch": 2.5,
7706
+ "learning_rate": 0.0002,
7707
+ "loss": 0.778,
7708
+ "step": 8100
7709
+ },
7710
+ {
7711
+ "epoch": 2.5,
7712
+ "learning_rate": 0.0002,
7713
+ "loss": 0.8003,
7714
+ "step": 8110
7715
+ },
7716
+ {
7717
+ "epoch": 2.51,
7718
+ "learning_rate": 0.0002,
7719
+ "loss": 0.7391,
7720
+ "step": 8120
7721
+ },
7722
+ {
7723
+ "epoch": 2.51,
7724
+ "learning_rate": 0.0002,
7725
+ "loss": 0.8281,
7726
+ "step": 8130
7727
+ },
7728
+ {
7729
+ "epoch": 2.51,
7730
+ "learning_rate": 0.0002,
7731
+ "loss": 0.7578,
7732
+ "step": 8140
7733
+ },
7734
+ {
7735
+ "epoch": 2.51,
7736
+ "learning_rate": 0.0002,
7737
+ "loss": 0.7331,
7738
+ "step": 8150
7739
+ },
7740
+ {
7741
+ "epoch": 2.52,
7742
+ "learning_rate": 0.0002,
7743
+ "loss": 0.6887,
7744
+ "step": 8160
7745
+ },
7746
+ {
7747
+ "epoch": 2.52,
7748
+ "learning_rate": 0.0002,
7749
+ "loss": 0.7411,
7750
+ "step": 8170
7751
+ },
7752
+ {
7753
+ "epoch": 2.52,
7754
+ "learning_rate": 0.0002,
7755
+ "loss": 0.7397,
7756
+ "step": 8180
7757
+ },
7758
+ {
7759
+ "epoch": 2.53,
7760
+ "learning_rate": 0.0002,
7761
+ "loss": 0.8129,
7762
+ "step": 8190
7763
+ },
7764
+ {
7765
+ "epoch": 2.53,
7766
+ "learning_rate": 0.0002,
7767
+ "loss": 0.7847,
7768
+ "step": 8200
7769
+ },
7770
+ {
7771
+ "epoch": 2.53,
7772
+ "eval_loss": 0.9241705536842346,
7773
+ "eval_runtime": 86.5391,
7774
+ "eval_samples_per_second": 11.555,
7775
+ "eval_steps_per_second": 5.778,
7776
+ "step": 8200
7777
+ },
7778
+ {
7779
+ "epoch": 2.53,
7780
+ "mmlu_eval_accuracy": 0.3909843422646258,
7781
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7782
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
7783
+ "mmlu_eval_accuracy_astronomy": 0.375,
7784
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7785
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
7786
+ "mmlu_eval_accuracy_college_biology": 0.375,
7787
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7788
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7789
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
7790
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
7791
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
7792
+ "mmlu_eval_accuracy_computer_security": 0.18181818181818182,
7793
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
7794
+ "mmlu_eval_accuracy_econometrics": 0.08333333333333333,
7795
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7796
+ "mmlu_eval_accuracy_elementary_mathematics": 0.21951219512195122,
7797
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
7798
+ "mmlu_eval_accuracy_global_facts": 0.3,
7799
+ "mmlu_eval_accuracy_high_school_biology": 0.34375,
7800
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
7801
+ "mmlu_eval_accuracy_high_school_computer_science": 0.4444444444444444,
7802
+ "mmlu_eval_accuracy_high_school_european_history": 0.5,
7803
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7804
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
7805
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
7806
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
7807
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
7808
+ "mmlu_eval_accuracy_high_school_physics": 0.058823529411764705,
7809
+ "mmlu_eval_accuracy_high_school_psychology": 0.5333333333333333,
7810
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
7811
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
7812
+ "mmlu_eval_accuracy_high_school_world_history": 0.5,
7813
+ "mmlu_eval_accuracy_human_aging": 0.5217391304347826,
7814
+ "mmlu_eval_accuracy_human_sexuality": 0.25,
7815
+ "mmlu_eval_accuracy_international_law": 0.6153846153846154,
7816
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
7817
+ "mmlu_eval_accuracy_logical_fallacies": 0.4444444444444444,
7818
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
7819
+ "mmlu_eval_accuracy_management": 0.45454545454545453,
7820
+ "mmlu_eval_accuracy_marketing": 0.76,
7821
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
7822
+ "mmlu_eval_accuracy_miscellaneous": 0.5116279069767442,
7823
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
7824
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
7825
+ "mmlu_eval_accuracy_nutrition": 0.42424242424242425,
7826
+ "mmlu_eval_accuracy_philosophy": 0.29411764705882354,
7827
+ "mmlu_eval_accuracy_prehistory": 0.4,
7828
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
7829
+ "mmlu_eval_accuracy_professional_law": 0.3235294117647059,
7830
+ "mmlu_eval_accuracy_professional_medicine": 0.3225806451612903,
7831
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
7832
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
7833
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7834
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
7835
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
7836
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7837
+ "mmlu_eval_accuracy_world_religions": 0.5789473684210527,
7838
+ "mmlu_loss": 1.7575427014429326,
7839
+ "step": 8200
7840
+ },
7841
+ {
7842
+ "epoch": 2.53,
7843
+ "learning_rate": 0.0002,
7844
+ "loss": 0.7145,
7845
+ "step": 8210
7846
+ },
7847
+ {
7848
+ "epoch": 2.54,
7849
+ "learning_rate": 0.0002,
7850
+ "loss": 0.813,
7851
+ "step": 8220
7852
+ },
7853
+ {
7854
+ "epoch": 2.54,
7855
+ "learning_rate": 0.0002,
7856
+ "loss": 0.7746,
7857
+ "step": 8230
7858
+ },
7859
+ {
7860
+ "epoch": 2.54,
7861
+ "learning_rate": 0.0002,
7862
+ "loss": 0.7671,
7863
+ "step": 8240
7864
+ },
7865
+ {
7866
+ "epoch": 2.55,
7867
+ "learning_rate": 0.0002,
7868
+ "loss": 0.7385,
7869
+ "step": 8250
7870
+ },
7871
+ {
7872
+ "epoch": 2.55,
7873
+ "learning_rate": 0.0002,
7874
+ "loss": 0.7658,
7875
+ "step": 8260
7876
+ },
7877
+ {
7878
+ "epoch": 2.55,
7879
+ "learning_rate": 0.0002,
7880
+ "loss": 0.7948,
7881
+ "step": 8270
7882
+ },
7883
+ {
7884
+ "epoch": 2.55,
7885
+ "learning_rate": 0.0002,
7886
+ "loss": 0.7677,
7887
+ "step": 8280
7888
+ },
7889
+ {
7890
+ "epoch": 2.56,
7891
+ "learning_rate": 0.0002,
7892
+ "loss": 0.7481,
7893
+ "step": 8290
7894
+ },
7895
+ {
7896
+ "epoch": 2.56,
7897
+ "learning_rate": 0.0002,
7898
+ "loss": 0.753,
7899
+ "step": 8300
7900
+ },
7901
+ {
7902
+ "epoch": 2.56,
7903
+ "learning_rate": 0.0002,
7904
+ "loss": 0.7793,
7905
+ "step": 8310
7906
+ },
7907
+ {
7908
+ "epoch": 2.57,
7909
+ "learning_rate": 0.0002,
7910
+ "loss": 0.754,
7911
+ "step": 8320
7912
+ },
7913
+ {
7914
+ "epoch": 2.57,
7915
+ "learning_rate": 0.0002,
7916
+ "loss": 0.7239,
7917
+ "step": 8330
7918
+ },
7919
+ {
7920
+ "epoch": 2.57,
7921
+ "learning_rate": 0.0002,
7922
+ "loss": 0.6884,
7923
+ "step": 8340
7924
+ },
7925
+ {
7926
+ "epoch": 2.58,
7927
+ "learning_rate": 0.0002,
7928
+ "loss": 0.7178,
7929
+ "step": 8350
7930
+ },
7931
+ {
7932
+ "epoch": 2.58,
7933
+ "learning_rate": 0.0002,
7934
+ "loss": 0.7357,
7935
+ "step": 8360
7936
+ },
7937
+ {
7938
+ "epoch": 2.58,
7939
+ "learning_rate": 0.0002,
7940
+ "loss": 0.7132,
7941
+ "step": 8370
7942
+ },
7943
+ {
7944
+ "epoch": 2.59,
7945
+ "learning_rate": 0.0002,
7946
+ "loss": 0.7616,
7947
+ "step": 8380
7948
+ },
7949
+ {
7950
+ "epoch": 2.59,
7951
+ "learning_rate": 0.0002,
7952
+ "loss": 0.7481,
7953
+ "step": 8390
7954
+ },
7955
+ {
7956
+ "epoch": 2.59,
7957
+ "learning_rate": 0.0002,
7958
+ "loss": 0.7328,
7959
+ "step": 8400
7960
+ },
7961
+ {
7962
+ "epoch": 2.59,
7963
+ "eval_loss": 0.9263262748718262,
7964
+ "eval_runtime": 85.6944,
7965
+ "eval_samples_per_second": 11.669,
7966
+ "eval_steps_per_second": 5.835,
7967
+ "step": 8400
7968
+ },
7969
+ {
7970
+ "epoch": 2.59,
7971
+ "mmlu_eval_accuracy": 0.38944178682072367,
7972
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7973
+ "mmlu_eval_accuracy_anatomy": 0.5,
7974
+ "mmlu_eval_accuracy_astronomy": 0.3125,
7975
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7976
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
7977
+ "mmlu_eval_accuracy_college_biology": 0.3125,
7978
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7979
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7980
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7981
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
7982
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7983
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
7984
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
7985
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
7986
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7987
+ "mmlu_eval_accuracy_elementary_mathematics": 0.21951219512195122,
7988
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
7989
+ "mmlu_eval_accuracy_global_facts": 0.2,
7990
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
7991
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
7992
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7993
+ "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
7994
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7995
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
7996
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.27906976744186046,
7997
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
7998
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6153846153846154,
7999
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8000
+ "mmlu_eval_accuracy_high_school_psychology": 0.5333333333333333,
8001
+ "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
8002
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
8003
+ "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
8004
+ "mmlu_eval_accuracy_human_aging": 0.43478260869565216,
8005
+ "mmlu_eval_accuracy_human_sexuality": 0.25,
8006
+ "mmlu_eval_accuracy_international_law": 0.5384615384615384,
8007
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8008
+ "mmlu_eval_accuracy_logical_fallacies": 0.4444444444444444,
8009
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
8010
+ "mmlu_eval_accuracy_management": 0.36363636363636365,
8011
+ "mmlu_eval_accuracy_marketing": 0.84,
8012
+ "mmlu_eval_accuracy_medical_genetics": 0.6363636363636364,
8013
+ "mmlu_eval_accuracy_miscellaneous": 0.5232558139534884,
8014
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
8015
+ "mmlu_eval_accuracy_moral_scenarios": 0.26,
8016
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
8017
+ "mmlu_eval_accuracy_philosophy": 0.2647058823529412,
8018
+ "mmlu_eval_accuracy_prehistory": 0.37142857142857144,
8019
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
8020
+ "mmlu_eval_accuracy_professional_law": 0.3058823529411765,
8021
+ "mmlu_eval_accuracy_professional_medicine": 0.25806451612903225,
8022
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
8023
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
8024
+ "mmlu_eval_accuracy_security_studies": 0.37037037037037035,
8025
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
8026
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
8027
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
8028
+ "mmlu_eval_accuracy_world_religions": 0.5263157894736842,
8029
+ "mmlu_loss": 1.766863293187114,
8030
+ "step": 8400
8031
+ },
8032
+ {
8033
+ "epoch": 2.59,
8034
+ "learning_rate": 0.0002,
8035
+ "loss": 0.7406,
8036
+ "step": 8410
8037
+ },
8038
+ {
8039
+ "epoch": 2.6,
8040
+ "learning_rate": 0.0002,
8041
+ "loss": 0.7688,
8042
+ "step": 8420
8043
+ },
8044
+ {
8045
+ "epoch": 2.6,
8046
+ "learning_rate": 0.0002,
8047
+ "loss": 0.7666,
8048
+ "step": 8430
8049
+ },
8050
+ {
8051
+ "epoch": 2.6,
8052
+ "learning_rate": 0.0002,
8053
+ "loss": 0.7338,
8054
+ "step": 8440
8055
+ },
8056
+ {
8057
+ "epoch": 2.61,
8058
+ "learning_rate": 0.0002,
8059
+ "loss": 0.814,
8060
+ "step": 8450
8061
+ },
8062
+ {
8063
+ "epoch": 2.61,
8064
+ "learning_rate": 0.0002,
8065
+ "loss": 0.8588,
8066
+ "step": 8460
8067
+ },
8068
+ {
8069
+ "epoch": 2.61,
8070
+ "learning_rate": 0.0002,
8071
+ "loss": 0.7684,
8072
+ "step": 8470
8073
+ },
8074
+ {
8075
+ "epoch": 2.62,
8076
+ "learning_rate": 0.0002,
8077
+ "loss": 0.763,
8078
+ "step": 8480
8079
+ },
8080
+ {
8081
+ "epoch": 2.62,
8082
+ "learning_rate": 0.0002,
8083
+ "loss": 0.7856,
8084
+ "step": 8490
8085
+ },
8086
+ {
8087
+ "epoch": 2.62,
8088
+ "learning_rate": 0.0002,
8089
+ "loss": 0.8017,
8090
+ "step": 8500
8091
+ },
8092
+ {
8093
+ "epoch": 2.63,
8094
+ "learning_rate": 0.0002,
8095
+ "loss": 0.7521,
8096
+ "step": 8510
8097
+ },
8098
+ {
8099
+ "epoch": 2.63,
8100
+ "learning_rate": 0.0002,
8101
+ "loss": 0.7883,
8102
+ "step": 8520
8103
+ },
8104
+ {
8105
+ "epoch": 2.63,
8106
+ "learning_rate": 0.0002,
8107
+ "loss": 0.7228,
8108
+ "step": 8530
8109
+ },
8110
+ {
8111
+ "epoch": 2.63,
8112
+ "learning_rate": 0.0002,
8113
+ "loss": 0.7749,
8114
+ "step": 8540
8115
+ },
8116
+ {
8117
+ "epoch": 2.64,
8118
+ "learning_rate": 0.0002,
8119
+ "loss": 0.7871,
8120
+ "step": 8550
8121
+ },
8122
+ {
8123
+ "epoch": 2.64,
8124
+ "learning_rate": 0.0002,
8125
+ "loss": 0.7498,
8126
+ "step": 8560
8127
+ },
8128
+ {
8129
+ "epoch": 2.64,
8130
+ "learning_rate": 0.0002,
8131
+ "loss": 0.7744,
8132
+ "step": 8570
8133
+ },
8134
+ {
8135
+ "epoch": 2.65,
8136
+ "learning_rate": 0.0002,
8137
+ "loss": 0.7834,
8138
+ "step": 8580
8139
+ },
8140
+ {
8141
+ "epoch": 2.65,
8142
+ "learning_rate": 0.0002,
8143
+ "loss": 0.8125,
8144
+ "step": 8590
8145
+ },
8146
+ {
8147
+ "epoch": 2.65,
8148
+ "learning_rate": 0.0002,
8149
+ "loss": 0.7567,
8150
+ "step": 8600
8151
+ },
8152
+ {
8153
+ "epoch": 2.65,
8154
+ "eval_loss": 0.9191973805427551,
8155
+ "eval_runtime": 85.7329,
8156
+ "eval_samples_per_second": 11.664,
8157
+ "eval_steps_per_second": 5.832,
8158
+ "step": 8600
8159
+ },
8160
+ {
8161
+ "epoch": 2.65,
8162
+ "mmlu_eval_accuracy": 0.3918413237852413,
8163
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
8164
+ "mmlu_eval_accuracy_anatomy": 0.42857142857142855,
8165
+ "mmlu_eval_accuracy_astronomy": 0.25,
8166
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
8167
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
8168
+ "mmlu_eval_accuracy_college_biology": 0.4375,
8169
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8170
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
8171
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8172
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
8173
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
8174
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
8175
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
8176
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
8177
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
8178
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2682926829268293,
8179
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
8180
+ "mmlu_eval_accuracy_global_facts": 0.2,
8181
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
8182
+ "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
8183
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8184
+ "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
8185
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8186
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.2857142857142857,
8187
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
8188
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
8189
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
8190
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8191
+ "mmlu_eval_accuracy_high_school_psychology": 0.5666666666666667,
8192
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
8193
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
8194
+ "mmlu_eval_accuracy_high_school_world_history": 0.5384615384615384,
8195
+ "mmlu_eval_accuracy_human_aging": 0.43478260869565216,
8196
+ "mmlu_eval_accuracy_human_sexuality": 0.16666666666666666,
8197
+ "mmlu_eval_accuracy_international_law": 0.46153846153846156,
8198
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
8199
+ "mmlu_eval_accuracy_logical_fallacies": 0.3333333333333333,
8200
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8201
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
8202
+ "mmlu_eval_accuracy_marketing": 0.8,
8203
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
8204
+ "mmlu_eval_accuracy_miscellaneous": 0.5116279069767442,
8205
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
8206
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
8207
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
8208
+ "mmlu_eval_accuracy_philosophy": 0.2647058823529412,
8209
+ "mmlu_eval_accuracy_prehistory": 0.37142857142857144,
8210
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
8211
+ "mmlu_eval_accuracy_professional_law": 0.31176470588235294,
8212
+ "mmlu_eval_accuracy_professional_medicine": 0.3225806451612903,
8213
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
8214
+ "mmlu_eval_accuracy_public_relations": 0.5,
8215
+ "mmlu_eval_accuracy_security_studies": 0.37037037037037035,
8216
+ "mmlu_eval_accuracy_sociology": 0.5454545454545454,
8217
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
8218
+ "mmlu_eval_accuracy_virology": 0.3888888888888889,
8219
+ "mmlu_eval_accuracy_world_religions": 0.47368421052631576,
8220
+ "mmlu_loss": 1.8475478451027882,
8221
+ "step": 8600
8222
+ },
8223
+ {
8224
+ "epoch": 2.66,
8225
+ "learning_rate": 0.0002,
8226
+ "loss": 0.8115,
8227
+ "step": 8610
8228
+ },
8229
+ {
8230
+ "epoch": 2.66,
8231
+ "learning_rate": 0.0002,
8232
+ "loss": 0.7661,
8233
+ "step": 8620
8234
+ },
8235
+ {
8236
+ "epoch": 2.66,
8237
+ "learning_rate": 0.0002,
8238
+ "loss": 0.7078,
8239
+ "step": 8630
8240
+ },
8241
+ {
8242
+ "epoch": 2.67,
8243
+ "learning_rate": 0.0002,
8244
+ "loss": 0.7772,
8245
+ "step": 8640
8246
+ },
8247
+ {
8248
+ "epoch": 2.67,
8249
+ "learning_rate": 0.0002,
8250
+ "loss": 0.7677,
8251
+ "step": 8650
8252
+ },
8253
+ {
8254
+ "epoch": 2.67,
8255
+ "learning_rate": 0.0002,
8256
+ "loss": 0.8279,
8257
+ "step": 8660
8258
+ },
8259
+ {
8260
+ "epoch": 2.68,
8261
+ "learning_rate": 0.0002,
8262
+ "loss": 0.7308,
8263
+ "step": 8670
8264
+ },
8265
+ {
8266
+ "epoch": 2.68,
8267
+ "learning_rate": 0.0002,
8268
+ "loss": 0.7727,
8269
+ "step": 8680
8270
+ },
8271
+ {
8272
+ "epoch": 2.68,
8273
+ "learning_rate": 0.0002,
8274
+ "loss": 0.7312,
8275
+ "step": 8690
8276
+ },
8277
+ {
8278
+ "epoch": 2.68,
8279
+ "learning_rate": 0.0002,
8280
+ "loss": 0.7648,
8281
+ "step": 8700
8282
+ },
8283
+ {
8284
+ "epoch": 2.69,
8285
+ "learning_rate": 0.0002,
8286
+ "loss": 0.8166,
8287
+ "step": 8710
8288
+ },
8289
+ {
8290
+ "epoch": 2.69,
8291
+ "learning_rate": 0.0002,
8292
+ "loss": 0.6678,
8293
+ "step": 8720
8294
+ },
8295
+ {
8296
+ "epoch": 2.69,
8297
+ "learning_rate": 0.0002,
8298
+ "loss": 0.7689,
8299
+ "step": 8730
8300
+ },
8301
+ {
8302
+ "epoch": 2.7,
8303
+ "learning_rate": 0.0002,
8304
+ "loss": 0.767,
8305
+ "step": 8740
8306
+ },
8307
+ {
8308
+ "epoch": 2.7,
8309
+ "learning_rate": 0.0002,
8310
+ "loss": 0.7906,
8311
+ "step": 8750
8312
+ },
8313
+ {
8314
+ "epoch": 2.7,
8315
+ "learning_rate": 0.0002,
8316
+ "loss": 0.7588,
8317
+ "step": 8760
8318
+ },
8319
+ {
8320
+ "epoch": 2.71,
8321
+ "learning_rate": 0.0002,
8322
+ "loss": 0.7503,
8323
+ "step": 8770
8324
+ },
8325
+ {
8326
+ "epoch": 2.71,
8327
+ "learning_rate": 0.0002,
8328
+ "loss": 0.7615,
8329
+ "step": 8780
8330
+ },
8331
+ {
8332
+ "epoch": 2.71,
8333
+ "learning_rate": 0.0002,
8334
+ "loss": 0.7851,
8335
+ "step": 8790
8336
+ },
8337
+ {
8338
+ "epoch": 2.72,
8339
+ "learning_rate": 0.0002,
8340
+ "loss": 0.7445,
8341
+ "step": 8800
8342
+ },
8343
+ {
8344
+ "epoch": 2.72,
8345
+ "eval_loss": 0.9140524864196777,
8346
+ "eval_runtime": 85.6829,
8347
+ "eval_samples_per_second": 11.671,
8348
+ "eval_steps_per_second": 5.835,
8349
+ "step": 8800
8350
+ },
8351
+ {
8352
+ "epoch": 2.72,
8353
+ "mmlu_eval_accuracy": 0.39694981591135137,
8354
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
8355
+ "mmlu_eval_accuracy_anatomy": 0.42857142857142855,
8356
+ "mmlu_eval_accuracy_astronomy": 0.25,
8357
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8358
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
8359
+ "mmlu_eval_accuracy_college_biology": 0.4375,
8360
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8361
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
8362
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8363
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
8364
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
8365
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
8366
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
8367
+ "mmlu_eval_accuracy_econometrics": 0.25,
8368
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
8369
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
8370
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
8371
+ "mmlu_eval_accuracy_global_facts": 0.3,
8372
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
8373
+ "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
8374
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8375
+ "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
8376
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
8377
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
8378
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
8379
+ "mmlu_eval_accuracy_high_school_mathematics": 0.3103448275862069,
8380
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6153846153846154,
8381
+ "mmlu_eval_accuracy_high_school_physics": 0.35294117647058826,
8382
+ "mmlu_eval_accuracy_high_school_psychology": 0.5666666666666667,
8383
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
8384
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
8385
+ "mmlu_eval_accuracy_high_school_world_history": 0.5769230769230769,
8386
+ "mmlu_eval_accuracy_human_aging": 0.4782608695652174,
8387
+ "mmlu_eval_accuracy_human_sexuality": 0.16666666666666666,
8388
+ "mmlu_eval_accuracy_international_law": 0.46153846153846156,
8389
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
8390
+ "mmlu_eval_accuracy_logical_fallacies": 0.3333333333333333,
8391
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8392
+ "mmlu_eval_accuracy_management": 0.45454545454545453,
8393
+ "mmlu_eval_accuracy_marketing": 0.76,
8394
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
8395
+ "mmlu_eval_accuracy_miscellaneous": 0.47674418604651164,
8396
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
8397
+ "mmlu_eval_accuracy_moral_scenarios": 0.26,
8398
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
8399
+ "mmlu_eval_accuracy_philosophy": 0.2647058823529412,
8400
+ "mmlu_eval_accuracy_prehistory": 0.34285714285714286,
8401
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
8402
+ "mmlu_eval_accuracy_professional_law": 0.3,
8403
+ "mmlu_eval_accuracy_professional_medicine": 0.2903225806451613,
8404
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
8405
+ "mmlu_eval_accuracy_public_relations": 0.5,
8406
+ "mmlu_eval_accuracy_security_studies": 0.37037037037037035,
8407
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
8408
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
8409
+ "mmlu_eval_accuracy_virology": 0.3888888888888889,
8410
+ "mmlu_eval_accuracy_world_religions": 0.5263157894736842,
8411
+ "mmlu_loss": 1.8303561169391513,
8412
+ "step": 8800
8413
+ },
8414
+ {
8415
+ "epoch": 2.72,
8416
+ "learning_rate": 0.0002,
8417
+ "loss": 0.805,
8418
+ "step": 8810
8419
+ },
8420
+ {
8421
+ "epoch": 2.72,
8422
+ "learning_rate": 0.0002,
8423
+ "loss": 0.7557,
8424
+ "step": 8820
8425
+ },
8426
+ {
8427
+ "epoch": 2.72,
8428
+ "learning_rate": 0.0002,
8429
+ "loss": 0.7943,
8430
+ "step": 8830
8431
+ },
8432
+ {
8433
+ "epoch": 2.73,
8434
+ "learning_rate": 0.0002,
8435
+ "loss": 0.7845,
8436
+ "step": 8840
8437
+ },
8438
+ {
8439
+ "epoch": 2.73,
8440
+ "learning_rate": 0.0002,
8441
+ "loss": 0.7829,
8442
+ "step": 8850
8443
+ },
8444
+ {
8445
+ "epoch": 2.73,
8446
+ "learning_rate": 0.0002,
8447
+ "loss": 0.6938,
8448
+ "step": 8860
8449
+ },
8450
+ {
8451
+ "epoch": 2.74,
8452
+ "learning_rate": 0.0002,
8453
+ "loss": 0.769,
8454
+ "step": 8870
8455
+ },
8456
+ {
8457
+ "epoch": 2.74,
8458
+ "learning_rate": 0.0002,
8459
+ "loss": 0.8187,
8460
+ "step": 8880
8461
+ },
8462
+ {
8463
+ "epoch": 2.74,
8464
+ "learning_rate": 0.0002,
8465
+ "loss": 0.7922,
8466
+ "step": 8890
8467
+ },
8468
+ {
8469
+ "epoch": 2.75,
8470
+ "learning_rate": 0.0002,
8471
+ "loss": 0.7718,
8472
+ "step": 8900
8473
+ },
8474
+ {
8475
+ "epoch": 2.75,
8476
+ "learning_rate": 0.0002,
8477
+ "loss": 0.7206,
8478
+ "step": 8910
8479
+ },
8480
+ {
8481
+ "epoch": 2.75,
8482
+ "learning_rate": 0.0002,
8483
+ "loss": 0.7241,
8484
+ "step": 8920
8485
+ },
8486
+ {
8487
+ "epoch": 2.76,
8488
+ "learning_rate": 0.0002,
8489
+ "loss": 0.7706,
8490
+ "step": 8930
8491
+ },
8492
+ {
8493
+ "epoch": 2.76,
8494
+ "learning_rate": 0.0002,
8495
+ "loss": 0.7282,
8496
+ "step": 8940
8497
+ },
8498
+ {
8499
+ "epoch": 2.76,
8500
+ "learning_rate": 0.0002,
8501
+ "loss": 0.7061,
8502
+ "step": 8950
8503
+ },
8504
+ {
8505
+ "epoch": 2.76,
8506
+ "learning_rate": 0.0002,
8507
+ "loss": 0.7747,
8508
+ "step": 8960
8509
+ },
8510
+ {
8511
+ "epoch": 2.77,
8512
+ "learning_rate": 0.0002,
8513
+ "loss": 0.7942,
8514
+ "step": 8970
8515
+ },
8516
+ {
8517
+ "epoch": 2.77,
8518
+ "learning_rate": 0.0002,
8519
+ "loss": 0.8133,
8520
+ "step": 8980
8521
+ },
8522
+ {
8523
+ "epoch": 2.77,
8524
+ "learning_rate": 0.0002,
8525
+ "loss": 0.7314,
8526
+ "step": 8990
8527
+ },
8528
+ {
8529
+ "epoch": 2.78,
8530
+ "learning_rate": 0.0002,
8531
+ "loss": 0.7373,
8532
+ "step": 9000
8533
+ },
8534
+ {
8535
+ "epoch": 2.78,
8536
+ "eval_loss": 0.9261744618415833,
8537
+ "eval_runtime": 85.7715,
8538
+ "eval_samples_per_second": 11.659,
8539
+ "eval_steps_per_second": 5.829,
8540
+ "step": 9000
8541
+ },
8542
+ {
8543
+ "epoch": 2.78,
8544
+ "mmlu_eval_accuracy": 0.39339554888194767,
8545
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
8546
+ "mmlu_eval_accuracy_anatomy": 0.42857142857142855,
8547
+ "mmlu_eval_accuracy_astronomy": 0.375,
8548
+ "mmlu_eval_accuracy_business_ethics": 0.2727272727272727,
8549
+ "mmlu_eval_accuracy_clinical_knowledge": 0.41379310344827586,
8550
+ "mmlu_eval_accuracy_college_biology": 0.375,
8551
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8552
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
8553
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
8554
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
8555
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
8556
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
8557
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
8558
+ "mmlu_eval_accuracy_econometrics": 0.25,
8559
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
8560
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
8561
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
8562
+ "mmlu_eval_accuracy_global_facts": 0.3,
8563
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
8564
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
8565
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8566
+ "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
8567
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
8568
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.23809523809523808,
8569
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3023255813953488,
8570
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
8571
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
8572
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8573
+ "mmlu_eval_accuracy_high_school_psychology": 0.5666666666666667,
8574
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
8575
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
8576
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
8577
+ "mmlu_eval_accuracy_human_aging": 0.5217391304347826,
8578
+ "mmlu_eval_accuracy_human_sexuality": 0.25,
8579
+ "mmlu_eval_accuracy_international_law": 0.46153846153846156,
8580
+ "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
8581
+ "mmlu_eval_accuracy_logical_fallacies": 0.3888888888888889,
8582
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
8583
+ "mmlu_eval_accuracy_management": 0.45454545454545453,
8584
+ "mmlu_eval_accuracy_marketing": 0.76,
8585
+ "mmlu_eval_accuracy_medical_genetics": 0.5454545454545454,
8586
+ "mmlu_eval_accuracy_miscellaneous": 0.5,
8587
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
8588
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
8589
+ "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
8590
+ "mmlu_eval_accuracy_philosophy": 0.2647058823529412,
8591
+ "mmlu_eval_accuracy_prehistory": 0.37142857142857144,
8592
+ "mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
8593
+ "mmlu_eval_accuracy_professional_law": 0.31176470588235294,
8594
+ "mmlu_eval_accuracy_professional_medicine": 0.2903225806451613,
8595
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8596
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
8597
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
8598
+ "mmlu_eval_accuracy_sociology": 0.5454545454545454,
8599
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
8600
+ "mmlu_eval_accuracy_virology": 0.3888888888888889,
8601
+ "mmlu_eval_accuracy_world_religions": 0.5263157894736842,
8602
+ "mmlu_loss": 1.8052426086393412,
8603
+ "step": 9000
8604
  }
8605
  ],
8606
  "max_steps": 10000,
8607
  "num_train_epochs": 4,
8608
+ "total_flos": 4.9480797123025306e+17,
8609
  "trial_name": null,
8610
  "trial_params": null
8611
  }
{checkpoint-7000 → checkpoint-9000}/training_args.bin RENAMED
File without changes