Farouk commited on
Commit
fefffee
·
1 Parent(s): 38fd34a

Training in progress, step 6000

Browse files
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:91c2f18577569044eb89ecec339c323a78fd6de382dd9f5c5c774a98f120e0dd
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34e9b01a0b4cb6fd7c0c3c26081ce5bb97e3e7ce5e57a00de45d3a2ed3fd9c6a
3
  size 319977229
checkpoint-3400/adapter_model/adapter_model/README.md CHANGED
@@ -125,6 +125,17 @@ The following `bitsandbytes` quantization config was used during training:
125
  - bnb_4bit_use_double_quant: True
126
  - bnb_4bit_compute_dtype: bfloat16
127
 
 
 
 
 
 
 
 
 
 
 
 
128
  The following `bitsandbytes` quantization config was used during training:
129
  - load_in_8bit: False
130
  - load_in_4bit: True
@@ -148,5 +159,6 @@ The following `bitsandbytes` quantization config was used during training:
148
  - PEFT 0.4.0
149
  - PEFT 0.4.0
150
  - PEFT 0.4.0
 
151
 
152
  - PEFT 0.4.0
 
125
  - bnb_4bit_use_double_quant: True
126
  - bnb_4bit_compute_dtype: bfloat16
127
 
128
+ The following `bitsandbytes` quantization config was used during training:
129
+ - load_in_8bit: False
130
+ - load_in_4bit: True
131
+ - llm_int8_threshold: 6.0
132
+ - llm_int8_skip_modules: None
133
+ - llm_int8_enable_fp32_cpu_offload: False
134
+ - llm_int8_has_fp16_weight: False
135
+ - bnb_4bit_quant_type: nf4
136
+ - bnb_4bit_use_double_quant: True
137
+ - bnb_4bit_compute_dtype: bfloat16
138
+
139
  The following `bitsandbytes` quantization config was used during training:
140
  - load_in_8bit: False
141
  - load_in_4bit: True
 
159
  - PEFT 0.4.0
160
  - PEFT 0.4.0
161
  - PEFT 0.4.0
162
+ - PEFT 0.4.0
163
 
164
  - PEFT 0.4.0
checkpoint-3400/adapter_model/adapter_model/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6f829eb59b020971a1553222f6b7cd3952af096f3b10e6766858c9123da066ed
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:91c2f18577569044eb89ecec339c323a78fd6de382dd9f5c5c774a98f120e0dd
3
  size 319977229
{checkpoint-4000 → checkpoint-6000}/README.md RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/adapter_config.json RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/adapter_model.bin RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:405f624ba283d73c5e163f13331b16b3af61c7a10aeb5759139ce20e013c733b
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34e9b01a0b4cb6fd7c0c3c26081ce5bb97e3e7ce5e57a00de45d3a2ed3fd9c6a
3
  size 319977229
{checkpoint-4000 → checkpoint-6000}/added_tokens.json RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/optimizer.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e75803e19a6e15b80ea37a00cc21b01247c27e1ea8f018ed0a8754ec28ca04d6
3
  size 1279539973
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3afc95c043a2cc88a8a642ced7d66602c52de0897048f21f1abb1c0fec9357ca
3
  size 1279539973
{checkpoint-4000 → checkpoint-6000}/rng_state.pth RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8341463efe819b77ffdc9a9813521647d84e527c34ee3e94ec5b9a68cff365d6
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:89db6f96789f9a8207a982b0707b344994d55a5738ff31632cb5b393156940c8
3
  size 14511
{checkpoint-4000 → checkpoint-6000}/scheduler.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:593f43b0c83adb27a2db37a6418c2ef12a213bbc2a02f2dc881de6846a69a931
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1d57105578b154c1429d6c6085dcbdd82165ec497fa3a0fd74932549f9aaac46
3
  size 627
{checkpoint-4000 → checkpoint-6000}/special_tokens_map.json RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/tokenizer.model RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/tokenizer_config.json RENAMED
File without changes
{checkpoint-4000 → checkpoint-6000}/trainer_state.json RENAMED
@@ -1,8 +1,8 @@
1
  {
2
  "best_metric": 0.8042147159576416,
3
  "best_model_checkpoint": "experts/expert-25/checkpoint-3400",
4
- "epoch": 1.164652787887611,
5
- "global_step": 4000,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
@@ -3826,11 +3826,1921 @@
3826
  "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
3827
  "mmlu_loss": 1.3634479641914368,
3828
  "step": 4000
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3829
  }
3830
  ],
3831
  "max_steps": 10000,
3832
  "num_train_epochs": 3,
3833
- "total_flos": 1.07727796733952e+18,
3834
  "trial_name": null,
3835
  "trial_params": null
3836
  }
 
1
  {
2
  "best_metric": 0.8042147159576416,
3
  "best_model_checkpoint": "experts/expert-25/checkpoint-3400",
4
+ "epoch": 1.7469791818314166,
5
+ "global_step": 6000,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
 
3826
  "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
3827
  "mmlu_loss": 1.3634479641914368,
3828
  "step": 4000
3829
+ },
3830
+ {
3831
+ "epoch": 1.17,
3832
+ "learning_rate": 0.0002,
3833
+ "loss": 0.919,
3834
+ "step": 4010
3835
+ },
3836
+ {
3837
+ "epoch": 1.17,
3838
+ "learning_rate": 0.0002,
3839
+ "loss": 0.8806,
3840
+ "step": 4020
3841
+ },
3842
+ {
3843
+ "epoch": 1.17,
3844
+ "learning_rate": 0.0002,
3845
+ "loss": 0.8799,
3846
+ "step": 4030
3847
+ },
3848
+ {
3849
+ "epoch": 1.18,
3850
+ "learning_rate": 0.0002,
3851
+ "loss": 0.8643,
3852
+ "step": 4040
3853
+ },
3854
+ {
3855
+ "epoch": 1.18,
3856
+ "learning_rate": 0.0002,
3857
+ "loss": 0.8289,
3858
+ "step": 4050
3859
+ },
3860
+ {
3861
+ "epoch": 1.18,
3862
+ "learning_rate": 0.0002,
3863
+ "loss": 0.844,
3864
+ "step": 4060
3865
+ },
3866
+ {
3867
+ "epoch": 1.19,
3868
+ "learning_rate": 0.0002,
3869
+ "loss": 0.8762,
3870
+ "step": 4070
3871
+ },
3872
+ {
3873
+ "epoch": 1.19,
3874
+ "learning_rate": 0.0002,
3875
+ "loss": 0.9243,
3876
+ "step": 4080
3877
+ },
3878
+ {
3879
+ "epoch": 1.19,
3880
+ "learning_rate": 0.0002,
3881
+ "loss": 0.9167,
3882
+ "step": 4090
3883
+ },
3884
+ {
3885
+ "epoch": 1.19,
3886
+ "learning_rate": 0.0002,
3887
+ "loss": 0.8258,
3888
+ "step": 4100
3889
+ },
3890
+ {
3891
+ "epoch": 1.2,
3892
+ "learning_rate": 0.0002,
3893
+ "loss": 0.8734,
3894
+ "step": 4110
3895
+ },
3896
+ {
3897
+ "epoch": 1.2,
3898
+ "learning_rate": 0.0002,
3899
+ "loss": 0.9008,
3900
+ "step": 4120
3901
+ },
3902
+ {
3903
+ "epoch": 1.2,
3904
+ "learning_rate": 0.0002,
3905
+ "loss": 0.891,
3906
+ "step": 4130
3907
+ },
3908
+ {
3909
+ "epoch": 1.21,
3910
+ "learning_rate": 0.0002,
3911
+ "loss": 0.8641,
3912
+ "step": 4140
3913
+ },
3914
+ {
3915
+ "epoch": 1.21,
3916
+ "learning_rate": 0.0002,
3917
+ "loss": 0.8145,
3918
+ "step": 4150
3919
+ },
3920
+ {
3921
+ "epoch": 1.21,
3922
+ "learning_rate": 0.0002,
3923
+ "loss": 0.7852,
3924
+ "step": 4160
3925
+ },
3926
+ {
3927
+ "epoch": 1.21,
3928
+ "learning_rate": 0.0002,
3929
+ "loss": 0.8739,
3930
+ "step": 4170
3931
+ },
3932
+ {
3933
+ "epoch": 1.22,
3934
+ "learning_rate": 0.0002,
3935
+ "loss": 0.8396,
3936
+ "step": 4180
3937
+ },
3938
+ {
3939
+ "epoch": 1.22,
3940
+ "learning_rate": 0.0002,
3941
+ "loss": 0.902,
3942
+ "step": 4190
3943
+ },
3944
+ {
3945
+ "epoch": 1.22,
3946
+ "learning_rate": 0.0002,
3947
+ "loss": 0.8656,
3948
+ "step": 4200
3949
+ },
3950
+ {
3951
+ "epoch": 1.22,
3952
+ "eval_loss": 0.8079001307487488,
3953
+ "eval_runtime": 112.1854,
3954
+ "eval_samples_per_second": 8.914,
3955
+ "eval_steps_per_second": 4.457,
3956
+ "step": 4200
3957
+ },
3958
+ {
3959
+ "epoch": 1.22,
3960
+ "mmlu_eval_accuracy": 0.5094746566834845,
3961
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
3962
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
3963
+ "mmlu_eval_accuracy_astronomy": 0.5625,
3964
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
3965
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
3966
+ "mmlu_eval_accuracy_college_biology": 0.4375,
3967
+ "mmlu_eval_accuracy_college_chemistry": 0.375,
3968
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
3969
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
3970
+ "mmlu_eval_accuracy_college_medicine": 0.5,
3971
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
3972
+ "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
3973
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
3974
+ "mmlu_eval_accuracy_econometrics": 0.25,
3975
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
3976
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
3977
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
3978
+ "mmlu_eval_accuracy_global_facts": 0.6,
3979
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
3980
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
3981
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
3982
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
3983
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
3984
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238,
3985
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
3986
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
3987
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
3988
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
3989
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
3990
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
3991
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
3992
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
3993
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
3994
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
3995
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
3996
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
3997
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
3998
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
3999
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
4000
+ "mmlu_eval_accuracy_marketing": 0.84,
4001
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
4002
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
4003
+ "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
4004
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
4005
+ "mmlu_eval_accuracy_nutrition": 0.696969696969697,
4006
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
4007
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
4008
+ "mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
4009
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
4010
+ "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
4011
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
4012
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
4013
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
4014
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
4015
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
4016
+ "mmlu_eval_accuracy_virology": 0.5,
4017
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
4018
+ "mmlu_loss": 1.4093773849794822,
4019
+ "step": 4200
4020
+ },
4021
+ {
4022
+ "epoch": 1.23,
4023
+ "learning_rate": 0.0002,
4024
+ "loss": 0.7718,
4025
+ "step": 4210
4026
+ },
4027
+ {
4028
+ "epoch": 1.23,
4029
+ "learning_rate": 0.0002,
4030
+ "loss": 0.8542,
4031
+ "step": 4220
4032
+ },
4033
+ {
4034
+ "epoch": 1.23,
4035
+ "learning_rate": 0.0002,
4036
+ "loss": 0.789,
4037
+ "step": 4230
4038
+ },
4039
+ {
4040
+ "epoch": 1.23,
4041
+ "learning_rate": 0.0002,
4042
+ "loss": 0.7869,
4043
+ "step": 4240
4044
+ },
4045
+ {
4046
+ "epoch": 1.24,
4047
+ "learning_rate": 0.0002,
4048
+ "loss": 0.7837,
4049
+ "step": 4250
4050
+ },
4051
+ {
4052
+ "epoch": 1.24,
4053
+ "learning_rate": 0.0002,
4054
+ "loss": 0.8693,
4055
+ "step": 4260
4056
+ },
4057
+ {
4058
+ "epoch": 1.24,
4059
+ "learning_rate": 0.0002,
4060
+ "loss": 0.8024,
4061
+ "step": 4270
4062
+ },
4063
+ {
4064
+ "epoch": 1.25,
4065
+ "learning_rate": 0.0002,
4066
+ "loss": 0.8672,
4067
+ "step": 4280
4068
+ },
4069
+ {
4070
+ "epoch": 1.25,
4071
+ "learning_rate": 0.0002,
4072
+ "loss": 0.8778,
4073
+ "step": 4290
4074
+ },
4075
+ {
4076
+ "epoch": 1.25,
4077
+ "learning_rate": 0.0002,
4078
+ "loss": 0.89,
4079
+ "step": 4300
4080
+ },
4081
+ {
4082
+ "epoch": 1.25,
4083
+ "learning_rate": 0.0002,
4084
+ "loss": 0.8435,
4085
+ "step": 4310
4086
+ },
4087
+ {
4088
+ "epoch": 1.26,
4089
+ "learning_rate": 0.0002,
4090
+ "loss": 0.9427,
4091
+ "step": 4320
4092
+ },
4093
+ {
4094
+ "epoch": 1.26,
4095
+ "learning_rate": 0.0002,
4096
+ "loss": 0.855,
4097
+ "step": 4330
4098
+ },
4099
+ {
4100
+ "epoch": 1.26,
4101
+ "learning_rate": 0.0002,
4102
+ "loss": 0.8827,
4103
+ "step": 4340
4104
+ },
4105
+ {
4106
+ "epoch": 1.27,
4107
+ "learning_rate": 0.0002,
4108
+ "loss": 0.8848,
4109
+ "step": 4350
4110
+ },
4111
+ {
4112
+ "epoch": 1.27,
4113
+ "learning_rate": 0.0002,
4114
+ "loss": 0.8016,
4115
+ "step": 4360
4116
+ },
4117
+ {
4118
+ "epoch": 1.27,
4119
+ "learning_rate": 0.0002,
4120
+ "loss": 0.9674,
4121
+ "step": 4370
4122
+ },
4123
+ {
4124
+ "epoch": 1.28,
4125
+ "learning_rate": 0.0002,
4126
+ "loss": 0.8914,
4127
+ "step": 4380
4128
+ },
4129
+ {
4130
+ "epoch": 1.28,
4131
+ "learning_rate": 0.0002,
4132
+ "loss": 0.8187,
4133
+ "step": 4390
4134
+ },
4135
+ {
4136
+ "epoch": 1.28,
4137
+ "learning_rate": 0.0002,
4138
+ "loss": 0.8518,
4139
+ "step": 4400
4140
+ },
4141
+ {
4142
+ "epoch": 1.28,
4143
+ "eval_loss": 0.8107084631919861,
4144
+ "eval_runtime": 112.0821,
4145
+ "eval_samples_per_second": 8.922,
4146
+ "eval_steps_per_second": 4.461,
4147
+ "step": 4400
4148
+ },
4149
+ {
4150
+ "epoch": 1.28,
4151
+ "mmlu_eval_accuracy": 0.5054326569126925,
4152
+ "mmlu_eval_accuracy_abstract_algebra": 0.45454545454545453,
4153
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
4154
+ "mmlu_eval_accuracy_astronomy": 0.5,
4155
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
4156
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
4157
+ "mmlu_eval_accuracy_college_biology": 0.5625,
4158
+ "mmlu_eval_accuracy_college_chemistry": 0.375,
4159
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
4160
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
4161
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
4162
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
4163
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
4164
+ "mmlu_eval_accuracy_conceptual_physics": 0.5384615384615384,
4165
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
4166
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
4167
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
4168
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
4169
+ "mmlu_eval_accuracy_global_facts": 0.5,
4170
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
4171
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
4172
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
4173
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
4174
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
4175
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
4176
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
4177
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
4178
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
4179
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
4180
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
4181
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
4182
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
4183
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
4184
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
4185
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
4186
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
4187
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
4188
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
4189
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
4190
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
4191
+ "mmlu_eval_accuracy_marketing": 0.84,
4192
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
4193
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
4194
+ "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
4195
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
4196
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
4197
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
4198
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
4199
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
4200
+ "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
4201
+ "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
4202
+ "mmlu_eval_accuracy_professional_psychology": 0.5072463768115942,
4203
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
4204
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
4205
+ "mmlu_eval_accuracy_sociology": 0.6363636363636364,
4206
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
4207
+ "mmlu_eval_accuracy_virology": 0.5,
4208
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
4209
+ "mmlu_loss": 1.3057481511532483,
4210
+ "step": 4400
4211
+ },
4212
+ {
4213
+ "epoch": 1.28,
4214
+ "learning_rate": 0.0002,
4215
+ "loss": 0.791,
4216
+ "step": 4410
4217
+ },
4218
+ {
4219
+ "epoch": 1.29,
4220
+ "learning_rate": 0.0002,
4221
+ "loss": 0.7682,
4222
+ "step": 4420
4223
+ },
4224
+ {
4225
+ "epoch": 1.29,
4226
+ "learning_rate": 0.0002,
4227
+ "loss": 0.7596,
4228
+ "step": 4430
4229
+ },
4230
+ {
4231
+ "epoch": 1.29,
4232
+ "learning_rate": 0.0002,
4233
+ "loss": 0.9505,
4234
+ "step": 4440
4235
+ },
4236
+ {
4237
+ "epoch": 1.3,
4238
+ "learning_rate": 0.0002,
4239
+ "loss": 0.8793,
4240
+ "step": 4450
4241
+ },
4242
+ {
4243
+ "epoch": 1.3,
4244
+ "learning_rate": 0.0002,
4245
+ "loss": 0.8468,
4246
+ "step": 4460
4247
+ },
4248
+ {
4249
+ "epoch": 1.3,
4250
+ "learning_rate": 0.0002,
4251
+ "loss": 0.8713,
4252
+ "step": 4470
4253
+ },
4254
+ {
4255
+ "epoch": 1.3,
4256
+ "learning_rate": 0.0002,
4257
+ "loss": 0.77,
4258
+ "step": 4480
4259
+ },
4260
+ {
4261
+ "epoch": 1.31,
4262
+ "learning_rate": 0.0002,
4263
+ "loss": 0.7419,
4264
+ "step": 4490
4265
+ },
4266
+ {
4267
+ "epoch": 1.31,
4268
+ "learning_rate": 0.0002,
4269
+ "loss": 0.928,
4270
+ "step": 4500
4271
+ },
4272
+ {
4273
+ "epoch": 1.31,
4274
+ "learning_rate": 0.0002,
4275
+ "loss": 0.8633,
4276
+ "step": 4510
4277
+ },
4278
+ {
4279
+ "epoch": 1.32,
4280
+ "learning_rate": 0.0002,
4281
+ "loss": 0.8111,
4282
+ "step": 4520
4283
+ },
4284
+ {
4285
+ "epoch": 1.32,
4286
+ "learning_rate": 0.0002,
4287
+ "loss": 0.8949,
4288
+ "step": 4530
4289
+ },
4290
+ {
4291
+ "epoch": 1.32,
4292
+ "learning_rate": 0.0002,
4293
+ "loss": 0.8427,
4294
+ "step": 4540
4295
+ },
4296
+ {
4297
+ "epoch": 1.32,
4298
+ "learning_rate": 0.0002,
4299
+ "loss": 0.8319,
4300
+ "step": 4550
4301
+ },
4302
+ {
4303
+ "epoch": 1.33,
4304
+ "learning_rate": 0.0002,
4305
+ "loss": 0.8146,
4306
+ "step": 4560
4307
+ },
4308
+ {
4309
+ "epoch": 1.33,
4310
+ "learning_rate": 0.0002,
4311
+ "loss": 0.8748,
4312
+ "step": 4570
4313
+ },
4314
+ {
4315
+ "epoch": 1.33,
4316
+ "learning_rate": 0.0002,
4317
+ "loss": 0.8075,
4318
+ "step": 4580
4319
+ },
4320
+ {
4321
+ "epoch": 1.34,
4322
+ "learning_rate": 0.0002,
4323
+ "loss": 0.9163,
4324
+ "step": 4590
4325
+ },
4326
+ {
4327
+ "epoch": 1.34,
4328
+ "learning_rate": 0.0002,
4329
+ "loss": 0.8485,
4330
+ "step": 4600
4331
+ },
4332
+ {
4333
+ "epoch": 1.34,
4334
+ "eval_loss": 0.8110213875770569,
4335
+ "eval_runtime": 112.2695,
4336
+ "eval_samples_per_second": 8.907,
4337
+ "eval_steps_per_second": 4.454,
4338
+ "step": 4600
4339
+ },
4340
+ {
4341
+ "epoch": 1.34,
4342
+ "mmlu_eval_accuracy": 0.5055979366091056,
4343
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
4344
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
4345
+ "mmlu_eval_accuracy_astronomy": 0.5,
4346
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
4347
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
4348
+ "mmlu_eval_accuracy_college_biology": 0.5,
4349
+ "mmlu_eval_accuracy_college_chemistry": 0.375,
4350
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
4351
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
4352
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
4353
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
4354
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
4355
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
4356
+ "mmlu_eval_accuracy_econometrics": 0.25,
4357
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
4358
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
4359
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
4360
+ "mmlu_eval_accuracy_global_facts": 0.6,
4361
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
4362
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
4363
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
4364
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
4365
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
4366
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
4367
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.46511627906976744,
4368
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
4369
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
4370
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
4371
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
4372
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
4373
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
4374
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
4375
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
4376
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
4377
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
4378
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
4379
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
4380
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
4381
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
4382
+ "mmlu_eval_accuracy_marketing": 0.84,
4383
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
4384
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
4385
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
4386
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
4387
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
4388
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
4389
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
4390
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
4391
+ "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
4392
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
4393
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
4394
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
4395
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
4396
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
4397
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
4398
+ "mmlu_eval_accuracy_virology": 0.5,
4399
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
4400
+ "mmlu_loss": 1.349465638749282,
4401
+ "step": 4600
4402
+ },
4403
+ {
4404
+ "epoch": 1.34,
4405
+ "learning_rate": 0.0002,
4406
+ "loss": 0.8501,
4407
+ "step": 4610
4408
+ },
4409
+ {
4410
+ "epoch": 1.35,
4411
+ "learning_rate": 0.0002,
4412
+ "loss": 0.8855,
4413
+ "step": 4620
4414
+ },
4415
+ {
4416
+ "epoch": 1.35,
4417
+ "learning_rate": 0.0002,
4418
+ "loss": 0.8735,
4419
+ "step": 4630
4420
+ },
4421
+ {
4422
+ "epoch": 1.35,
4423
+ "learning_rate": 0.0002,
4424
+ "loss": 0.7924,
4425
+ "step": 4640
4426
+ },
4427
+ {
4428
+ "epoch": 1.35,
4429
+ "learning_rate": 0.0002,
4430
+ "loss": 0.8629,
4431
+ "step": 4650
4432
+ },
4433
+ {
4434
+ "epoch": 1.36,
4435
+ "learning_rate": 0.0002,
4436
+ "loss": 0.9271,
4437
+ "step": 4660
4438
+ },
4439
+ {
4440
+ "epoch": 1.36,
4441
+ "learning_rate": 0.0002,
4442
+ "loss": 0.8608,
4443
+ "step": 4670
4444
+ },
4445
+ {
4446
+ "epoch": 1.36,
4447
+ "learning_rate": 0.0002,
4448
+ "loss": 0.8287,
4449
+ "step": 4680
4450
+ },
4451
+ {
4452
+ "epoch": 1.37,
4453
+ "learning_rate": 0.0002,
4454
+ "loss": 0.8546,
4455
+ "step": 4690
4456
+ },
4457
+ {
4458
+ "epoch": 1.37,
4459
+ "learning_rate": 0.0002,
4460
+ "loss": 0.8212,
4461
+ "step": 4700
4462
+ },
4463
+ {
4464
+ "epoch": 1.37,
4465
+ "learning_rate": 0.0002,
4466
+ "loss": 0.8831,
4467
+ "step": 4710
4468
+ },
4469
+ {
4470
+ "epoch": 1.37,
4471
+ "learning_rate": 0.0002,
4472
+ "loss": 0.8255,
4473
+ "step": 4720
4474
+ },
4475
+ {
4476
+ "epoch": 1.38,
4477
+ "learning_rate": 0.0002,
4478
+ "loss": 0.8641,
4479
+ "step": 4730
4480
+ },
4481
+ {
4482
+ "epoch": 1.38,
4483
+ "learning_rate": 0.0002,
4484
+ "loss": 0.8731,
4485
+ "step": 4740
4486
+ },
4487
+ {
4488
+ "epoch": 1.38,
4489
+ "learning_rate": 0.0002,
4490
+ "loss": 0.8085,
4491
+ "step": 4750
4492
+ },
4493
+ {
4494
+ "epoch": 1.39,
4495
+ "learning_rate": 0.0002,
4496
+ "loss": 0.9141,
4497
+ "step": 4760
4498
+ },
4499
+ {
4500
+ "epoch": 1.39,
4501
+ "learning_rate": 0.0002,
4502
+ "loss": 0.8443,
4503
+ "step": 4770
4504
+ },
4505
+ {
4506
+ "epoch": 1.39,
4507
+ "learning_rate": 0.0002,
4508
+ "loss": 0.8085,
4509
+ "step": 4780
4510
+ },
4511
+ {
4512
+ "epoch": 1.39,
4513
+ "learning_rate": 0.0002,
4514
+ "loss": 0.8494,
4515
+ "step": 4790
4516
+ },
4517
+ {
4518
+ "epoch": 1.4,
4519
+ "learning_rate": 0.0002,
4520
+ "loss": 0.84,
4521
+ "step": 4800
4522
+ },
4523
+ {
4524
+ "epoch": 1.4,
4525
+ "eval_loss": 0.8135509490966797,
4526
+ "eval_runtime": 112.3978,
4527
+ "eval_samples_per_second": 8.897,
4528
+ "eval_steps_per_second": 4.448,
4529
+ "step": 4800
4530
+ },
4531
+ {
4532
+ "epoch": 1.4,
4533
+ "mmlu_eval_accuracy": 0.4998311163494409,
4534
+ "mmlu_eval_accuracy_abstract_algebra": 0.45454545454545453,
4535
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
4536
+ "mmlu_eval_accuracy_astronomy": 0.5625,
4537
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
4538
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
4539
+ "mmlu_eval_accuracy_college_biology": 0.5,
4540
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
4541
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
4542
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
4543
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
4544
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
4545
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
4546
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
4547
+ "mmlu_eval_accuracy_econometrics": 0.25,
4548
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
4549
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
4550
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
4551
+ "mmlu_eval_accuracy_global_facts": 0.5,
4552
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
4553
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
4554
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
4555
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
4556
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
4557
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
4558
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
4559
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
4560
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
4561
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
4562
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
4563
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
4564
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
4565
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
4566
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
4567
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
4568
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
4569
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
4570
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
4571
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
4572
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
4573
+ "mmlu_eval_accuracy_marketing": 0.84,
4574
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
4575
+ "mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
4576
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
4577
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
4578
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
4579
+ "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
4580
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
4581
+ "mmlu_eval_accuracy_professional_accounting": 0.3870967741935484,
4582
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
4583
+ "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
4584
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
4585
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
4586
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
4587
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
4588
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
4589
+ "mmlu_eval_accuracy_virology": 0.5,
4590
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
4591
+ "mmlu_loss": 1.3253662804477209,
4592
+ "step": 4800
4593
+ },
4594
+ {
4595
+ "epoch": 1.4,
4596
+ "learning_rate": 0.0002,
4597
+ "loss": 0.842,
4598
+ "step": 4810
4599
+ },
4600
+ {
4601
+ "epoch": 1.4,
4602
+ "learning_rate": 0.0002,
4603
+ "loss": 0.8867,
4604
+ "step": 4820
4605
+ },
4606
+ {
4607
+ "epoch": 1.41,
4608
+ "learning_rate": 0.0002,
4609
+ "loss": 0.7843,
4610
+ "step": 4830
4611
+ },
4612
+ {
4613
+ "epoch": 1.41,
4614
+ "learning_rate": 0.0002,
4615
+ "loss": 0.6769,
4616
+ "step": 4840
4617
+ },
4618
+ {
4619
+ "epoch": 1.41,
4620
+ "learning_rate": 0.0002,
4621
+ "loss": 0.8129,
4622
+ "step": 4850
4623
+ },
4624
+ {
4625
+ "epoch": 1.42,
4626
+ "learning_rate": 0.0002,
4627
+ "loss": 0.7671,
4628
+ "step": 4860
4629
+ },
4630
+ {
4631
+ "epoch": 1.42,
4632
+ "learning_rate": 0.0002,
4633
+ "loss": 0.7459,
4634
+ "step": 4870
4635
+ },
4636
+ {
4637
+ "epoch": 1.42,
4638
+ "learning_rate": 0.0002,
4639
+ "loss": 0.8878,
4640
+ "step": 4880
4641
+ },
4642
+ {
4643
+ "epoch": 1.42,
4644
+ "learning_rate": 0.0002,
4645
+ "loss": 0.8404,
4646
+ "step": 4890
4647
+ },
4648
+ {
4649
+ "epoch": 1.43,
4650
+ "learning_rate": 0.0002,
4651
+ "loss": 0.7844,
4652
+ "step": 4900
4653
+ },
4654
+ {
4655
+ "epoch": 1.43,
4656
+ "learning_rate": 0.0002,
4657
+ "loss": 0.8549,
4658
+ "step": 4910
4659
+ },
4660
+ {
4661
+ "epoch": 1.43,
4662
+ "learning_rate": 0.0002,
4663
+ "loss": 0.9099,
4664
+ "step": 4920
4665
+ },
4666
+ {
4667
+ "epoch": 1.44,
4668
+ "learning_rate": 0.0002,
4669
+ "loss": 0.833,
4670
+ "step": 4930
4671
+ },
4672
+ {
4673
+ "epoch": 1.44,
4674
+ "learning_rate": 0.0002,
4675
+ "loss": 0.9135,
4676
+ "step": 4940
4677
+ },
4678
+ {
4679
+ "epoch": 1.44,
4680
+ "learning_rate": 0.0002,
4681
+ "loss": 0.7573,
4682
+ "step": 4950
4683
+ },
4684
+ {
4685
+ "epoch": 1.44,
4686
+ "learning_rate": 0.0002,
4687
+ "loss": 0.9444,
4688
+ "step": 4960
4689
+ },
4690
+ {
4691
+ "epoch": 1.45,
4692
+ "learning_rate": 0.0002,
4693
+ "loss": 0.8831,
4694
+ "step": 4970
4695
+ },
4696
+ {
4697
+ "epoch": 1.45,
4698
+ "learning_rate": 0.0002,
4699
+ "loss": 0.8842,
4700
+ "step": 4980
4701
+ },
4702
+ {
4703
+ "epoch": 1.45,
4704
+ "learning_rate": 0.0002,
4705
+ "loss": 0.8501,
4706
+ "step": 4990
4707
+ },
4708
+ {
4709
+ "epoch": 1.46,
4710
+ "learning_rate": 0.0002,
4711
+ "loss": 0.8653,
4712
+ "step": 5000
4713
+ },
4714
+ {
4715
+ "epoch": 1.46,
4716
+ "eval_loss": 0.8124507665634155,
4717
+ "eval_runtime": 112.4014,
4718
+ "eval_samples_per_second": 8.897,
4719
+ "eval_steps_per_second": 4.448,
4720
+ "step": 5000
4721
+ },
4722
+ {
4723
+ "epoch": 1.46,
4724
+ "mmlu_eval_accuracy": 0.49611962914206076,
4725
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
4726
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
4727
+ "mmlu_eval_accuracy_astronomy": 0.5625,
4728
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
4729
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
4730
+ "mmlu_eval_accuracy_college_biology": 0.5625,
4731
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
4732
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
4733
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
4734
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
4735
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
4736
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
4737
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
4738
+ "mmlu_eval_accuracy_econometrics": 0.25,
4739
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
4740
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
4741
+ "mmlu_eval_accuracy_formal_logic": 0.07142857142857142,
4742
+ "mmlu_eval_accuracy_global_facts": 0.5,
4743
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
4744
+ "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
4745
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
4746
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
4747
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
4748
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
4749
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
4750
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
4751
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
4752
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
4753
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
4754
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
4755
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
4756
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
4757
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
4758
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
4759
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
4760
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
4761
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
4762
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
4763
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
4764
+ "mmlu_eval_accuracy_marketing": 0.8,
4765
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
4766
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
4767
+ "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
4768
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
4769
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
4770
+ "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
4771
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
4772
+ "mmlu_eval_accuracy_professional_accounting": 0.41935483870967744,
4773
+ "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
4774
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
4775
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
4776
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
4777
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
4778
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
4779
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
4780
+ "mmlu_eval_accuracy_virology": 0.5,
4781
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
4782
+ "mmlu_loss": 1.3226010548072447,
4783
+ "step": 5000
4784
+ },
4785
+ {
4786
+ "epoch": 1.46,
4787
+ "learning_rate": 0.0002,
4788
+ "loss": 0.9205,
4789
+ "step": 5010
4790
+ },
4791
+ {
4792
+ "epoch": 1.46,
4793
+ "learning_rate": 0.0002,
4794
+ "loss": 0.7774,
4795
+ "step": 5020
4796
+ },
4797
+ {
4798
+ "epoch": 1.46,
4799
+ "learning_rate": 0.0002,
4800
+ "loss": 0.7829,
4801
+ "step": 5030
4802
+ },
4803
+ {
4804
+ "epoch": 1.47,
4805
+ "learning_rate": 0.0002,
4806
+ "loss": 0.8501,
4807
+ "step": 5040
4808
+ },
4809
+ {
4810
+ "epoch": 1.47,
4811
+ "learning_rate": 0.0002,
4812
+ "loss": 0.8622,
4813
+ "step": 5050
4814
+ },
4815
+ {
4816
+ "epoch": 1.47,
4817
+ "learning_rate": 0.0002,
4818
+ "loss": 0.7971,
4819
+ "step": 5060
4820
+ },
4821
+ {
4822
+ "epoch": 1.48,
4823
+ "learning_rate": 0.0002,
4824
+ "loss": 0.8705,
4825
+ "step": 5070
4826
+ },
4827
+ {
4828
+ "epoch": 1.48,
4829
+ "learning_rate": 0.0002,
4830
+ "loss": 0.8234,
4831
+ "step": 5080
4832
+ },
4833
+ {
4834
+ "epoch": 1.48,
4835
+ "learning_rate": 0.0002,
4836
+ "loss": 0.8872,
4837
+ "step": 5090
4838
+ },
4839
+ {
4840
+ "epoch": 1.48,
4841
+ "learning_rate": 0.0002,
4842
+ "loss": 0.8901,
4843
+ "step": 5100
4844
+ },
4845
+ {
4846
+ "epoch": 1.49,
4847
+ "learning_rate": 0.0002,
4848
+ "loss": 0.8731,
4849
+ "step": 5110
4850
+ },
4851
+ {
4852
+ "epoch": 1.49,
4853
+ "learning_rate": 0.0002,
4854
+ "loss": 0.8599,
4855
+ "step": 5120
4856
+ },
4857
+ {
4858
+ "epoch": 1.49,
4859
+ "learning_rate": 0.0002,
4860
+ "loss": 0.8223,
4861
+ "step": 5130
4862
+ },
4863
+ {
4864
+ "epoch": 1.5,
4865
+ "learning_rate": 0.0002,
4866
+ "loss": 0.8619,
4867
+ "step": 5140
4868
+ },
4869
+ {
4870
+ "epoch": 1.5,
4871
+ "learning_rate": 0.0002,
4872
+ "loss": 0.8746,
4873
+ "step": 5150
4874
+ },
4875
+ {
4876
+ "epoch": 1.5,
4877
+ "learning_rate": 0.0002,
4878
+ "loss": 0.8987,
4879
+ "step": 5160
4880
+ },
4881
+ {
4882
+ "epoch": 1.51,
4883
+ "learning_rate": 0.0002,
4884
+ "loss": 0.7756,
4885
+ "step": 5170
4886
+ },
4887
+ {
4888
+ "epoch": 1.51,
4889
+ "learning_rate": 0.0002,
4890
+ "loss": 0.8282,
4891
+ "step": 5180
4892
+ },
4893
+ {
4894
+ "epoch": 1.51,
4895
+ "learning_rate": 0.0002,
4896
+ "loss": 0.8271,
4897
+ "step": 5190
4898
+ },
4899
+ {
4900
+ "epoch": 1.51,
4901
+ "learning_rate": 0.0002,
4902
+ "loss": 0.8014,
4903
+ "step": 5200
4904
+ },
4905
+ {
4906
+ "epoch": 1.51,
4907
+ "eval_loss": 0.8068380355834961,
4908
+ "eval_runtime": 112.0243,
4909
+ "eval_samples_per_second": 8.927,
4910
+ "eval_steps_per_second": 4.463,
4911
+ "step": 5200
4912
+ },
4913
+ {
4914
+ "epoch": 1.51,
4915
+ "mmlu_eval_accuracy": 0.494753529535565,
4916
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
4917
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
4918
+ "mmlu_eval_accuracy_astronomy": 0.5,
4919
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
4920
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
4921
+ "mmlu_eval_accuracy_college_biology": 0.5,
4922
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
4923
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
4924
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
4925
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
4926
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
4927
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
4928
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
4929
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
4930
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
4931
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
4932
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
4933
+ "mmlu_eval_accuracy_global_facts": 0.5,
4934
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
4935
+ "mmlu_eval_accuracy_high_school_chemistry": 0.22727272727272727,
4936
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
4937
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
4938
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
4939
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
4940
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
4941
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
4942
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
4943
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
4944
+ "mmlu_eval_accuracy_high_school_psychology": 0.8833333333333333,
4945
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
4946
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
4947
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
4948
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
4949
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
4950
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
4951
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
4952
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
4953
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
4954
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
4955
+ "mmlu_eval_accuracy_marketing": 0.84,
4956
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
4957
+ "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
4958
+ "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
4959
+ "mmlu_eval_accuracy_moral_scenarios": 0.29,
4960
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
4961
+ "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
4962
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
4963
+ "mmlu_eval_accuracy_professional_accounting": 0.45161290322580644,
4964
+ "mmlu_eval_accuracy_professional_law": 0.35294117647058826,
4965
+ "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
4966
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
4967
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
4968
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
4969
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
4970
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
4971
+ "mmlu_eval_accuracy_virology": 0.5,
4972
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
4973
+ "mmlu_loss": 1.363197118822028,
4974
+ "step": 5200
4975
+ },
4976
+ {
4977
+ "epoch": 1.52,
4978
+ "learning_rate": 0.0002,
4979
+ "loss": 0.8763,
4980
+ "step": 5210
4981
+ },
4982
+ {
4983
+ "epoch": 1.52,
4984
+ "learning_rate": 0.0002,
4985
+ "loss": 0.8323,
4986
+ "step": 5220
4987
+ },
4988
+ {
4989
+ "epoch": 1.52,
4990
+ "learning_rate": 0.0002,
4991
+ "loss": 0.8509,
4992
+ "step": 5230
4993
+ },
4994
+ {
4995
+ "epoch": 1.53,
4996
+ "learning_rate": 0.0002,
4997
+ "loss": 0.8351,
4998
+ "step": 5240
4999
+ },
5000
+ {
5001
+ "epoch": 1.53,
5002
+ "learning_rate": 0.0002,
5003
+ "loss": 0.87,
5004
+ "step": 5250
5005
+ },
5006
+ {
5007
+ "epoch": 1.53,
5008
+ "learning_rate": 0.0002,
5009
+ "loss": 0.7947,
5010
+ "step": 5260
5011
+ },
5012
+ {
5013
+ "epoch": 1.53,
5014
+ "learning_rate": 0.0002,
5015
+ "loss": 0.7707,
5016
+ "step": 5270
5017
+ },
5018
+ {
5019
+ "epoch": 1.54,
5020
+ "learning_rate": 0.0002,
5021
+ "loss": 0.8457,
5022
+ "step": 5280
5023
+ },
5024
+ {
5025
+ "epoch": 1.54,
5026
+ "learning_rate": 0.0002,
5027
+ "loss": 0.8234,
5028
+ "step": 5290
5029
+ },
5030
+ {
5031
+ "epoch": 1.54,
5032
+ "learning_rate": 0.0002,
5033
+ "loss": 0.8129,
5034
+ "step": 5300
5035
+ },
5036
+ {
5037
+ "epoch": 1.55,
5038
+ "learning_rate": 0.0002,
5039
+ "loss": 0.8793,
5040
+ "step": 5310
5041
+ },
5042
+ {
5043
+ "epoch": 1.55,
5044
+ "learning_rate": 0.0002,
5045
+ "loss": 0.8009,
5046
+ "step": 5320
5047
+ },
5048
+ {
5049
+ "epoch": 1.55,
5050
+ "learning_rate": 0.0002,
5051
+ "loss": 0.9667,
5052
+ "step": 5330
5053
+ },
5054
+ {
5055
+ "epoch": 1.55,
5056
+ "learning_rate": 0.0002,
5057
+ "loss": 0.7834,
5058
+ "step": 5340
5059
+ },
5060
+ {
5061
+ "epoch": 1.56,
5062
+ "learning_rate": 0.0002,
5063
+ "loss": 0.7376,
5064
+ "step": 5350
5065
+ },
5066
+ {
5067
+ "epoch": 1.56,
5068
+ "learning_rate": 0.0002,
5069
+ "loss": 0.795,
5070
+ "step": 5360
5071
+ },
5072
+ {
5073
+ "epoch": 1.56,
5074
+ "learning_rate": 0.0002,
5075
+ "loss": 0.8667,
5076
+ "step": 5370
5077
+ },
5078
+ {
5079
+ "epoch": 1.57,
5080
+ "learning_rate": 0.0002,
5081
+ "loss": 0.8208,
5082
+ "step": 5380
5083
+ },
5084
+ {
5085
+ "epoch": 1.57,
5086
+ "learning_rate": 0.0002,
5087
+ "loss": 0.88,
5088
+ "step": 5390
5089
+ },
5090
+ {
5091
+ "epoch": 1.57,
5092
+ "learning_rate": 0.0002,
5093
+ "loss": 0.8099,
5094
+ "step": 5400
5095
+ },
5096
+ {
5097
+ "epoch": 1.57,
5098
+ "eval_loss": 0.8074617981910706,
5099
+ "eval_runtime": 112.4792,
5100
+ "eval_samples_per_second": 8.891,
5101
+ "eval_steps_per_second": 4.445,
5102
+ "step": 5400
5103
+ },
5104
+ {
5105
+ "epoch": 1.57,
5106
+ "mmlu_eval_accuracy": 0.49947322987276316,
5107
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
5108
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
5109
+ "mmlu_eval_accuracy_astronomy": 0.5625,
5110
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
5111
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
5112
+ "mmlu_eval_accuracy_college_biology": 0.5,
5113
+ "mmlu_eval_accuracy_college_chemistry": 0.375,
5114
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
5115
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
5116
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
5117
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
5118
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
5119
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
5120
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
5121
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
5122
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
5123
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
5124
+ "mmlu_eval_accuracy_global_facts": 0.5,
5125
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
5126
+ "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
5127
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5128
+ "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
5129
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
5130
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
5131
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
5132
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
5133
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
5134
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
5135
+ "mmlu_eval_accuracy_high_school_psychology": 0.8833333333333333,
5136
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
5137
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5138
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
5139
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
5140
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
5141
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
5142
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
5143
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
5144
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
5145
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
5146
+ "mmlu_eval_accuracy_marketing": 0.84,
5147
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
5148
+ "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
5149
+ "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
5150
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
5151
+ "mmlu_eval_accuracy_nutrition": 0.696969696969697,
5152
+ "mmlu_eval_accuracy_philosophy": 0.5,
5153
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
5154
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
5155
+ "mmlu_eval_accuracy_professional_law": 0.3411764705882353,
5156
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
5157
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
5158
+ "mmlu_eval_accuracy_public_relations": 0.5,
5159
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
5160
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
5161
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
5162
+ "mmlu_eval_accuracy_virology": 0.5,
5163
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
5164
+ "mmlu_loss": 1.2389598589964386,
5165
+ "step": 5400
5166
+ },
5167
+ {
5168
+ "epoch": 1.58,
5169
+ "learning_rate": 0.0002,
5170
+ "loss": 0.8101,
5171
+ "step": 5410
5172
+ },
5173
+ {
5174
+ "epoch": 1.58,
5175
+ "learning_rate": 0.0002,
5176
+ "loss": 0.8081,
5177
+ "step": 5420
5178
+ },
5179
+ {
5180
+ "epoch": 1.58,
5181
+ "learning_rate": 0.0002,
5182
+ "loss": 0.8398,
5183
+ "step": 5430
5184
+ },
5185
+ {
5186
+ "epoch": 1.58,
5187
+ "learning_rate": 0.0002,
5188
+ "loss": 0.8397,
5189
+ "step": 5440
5190
+ },
5191
+ {
5192
+ "epoch": 1.59,
5193
+ "learning_rate": 0.0002,
5194
+ "loss": 0.8135,
5195
+ "step": 5450
5196
+ },
5197
+ {
5198
+ "epoch": 1.59,
5199
+ "learning_rate": 0.0002,
5200
+ "loss": 0.8382,
5201
+ "step": 5460
5202
+ },
5203
+ {
5204
+ "epoch": 1.59,
5205
+ "learning_rate": 0.0002,
5206
+ "loss": 0.8801,
5207
+ "step": 5470
5208
+ },
5209
+ {
5210
+ "epoch": 1.6,
5211
+ "learning_rate": 0.0002,
5212
+ "loss": 0.8888,
5213
+ "step": 5480
5214
+ },
5215
+ {
5216
+ "epoch": 1.6,
5217
+ "learning_rate": 0.0002,
5218
+ "loss": 0.8372,
5219
+ "step": 5490
5220
+ },
5221
+ {
5222
+ "epoch": 1.6,
5223
+ "learning_rate": 0.0002,
5224
+ "loss": 0.8744,
5225
+ "step": 5500
5226
+ },
5227
+ {
5228
+ "epoch": 1.6,
5229
+ "learning_rate": 0.0002,
5230
+ "loss": 0.8068,
5231
+ "step": 5510
5232
+ },
5233
+ {
5234
+ "epoch": 1.61,
5235
+ "learning_rate": 0.0002,
5236
+ "loss": 0.8402,
5237
+ "step": 5520
5238
+ },
5239
+ {
5240
+ "epoch": 1.61,
5241
+ "learning_rate": 0.0002,
5242
+ "loss": 0.8665,
5243
+ "step": 5530
5244
+ },
5245
+ {
5246
+ "epoch": 1.61,
5247
+ "learning_rate": 0.0002,
5248
+ "loss": 0.8625,
5249
+ "step": 5540
5250
+ },
5251
+ {
5252
+ "epoch": 1.62,
5253
+ "learning_rate": 0.0002,
5254
+ "loss": 0.7599,
5255
+ "step": 5550
5256
+ },
5257
+ {
5258
+ "epoch": 1.62,
5259
+ "learning_rate": 0.0002,
5260
+ "loss": 0.8044,
5261
+ "step": 5560
5262
+ },
5263
+ {
5264
+ "epoch": 1.62,
5265
+ "learning_rate": 0.0002,
5266
+ "loss": 0.8461,
5267
+ "step": 5570
5268
+ },
5269
+ {
5270
+ "epoch": 1.62,
5271
+ "learning_rate": 0.0002,
5272
+ "loss": 0.8375,
5273
+ "step": 5580
5274
+ },
5275
+ {
5276
+ "epoch": 1.63,
5277
+ "learning_rate": 0.0002,
5278
+ "loss": 0.8686,
5279
+ "step": 5590
5280
+ },
5281
+ {
5282
+ "epoch": 1.63,
5283
+ "learning_rate": 0.0002,
5284
+ "loss": 0.7484,
5285
+ "step": 5600
5286
+ },
5287
+ {
5288
+ "epoch": 1.63,
5289
+ "eval_loss": 0.8066723346710205,
5290
+ "eval_runtime": 113.3502,
5291
+ "eval_samples_per_second": 8.822,
5292
+ "eval_steps_per_second": 4.411,
5293
+ "step": 5600
5294
+ },
5295
+ {
5296
+ "epoch": 1.63,
5297
+ "mmlu_eval_accuracy": 0.5038582219158022,
5298
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
5299
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
5300
+ "mmlu_eval_accuracy_astronomy": 0.5,
5301
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
5302
+ "mmlu_eval_accuracy_clinical_knowledge": 0.6206896551724138,
5303
+ "mmlu_eval_accuracy_college_biology": 0.4375,
5304
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
5305
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
5306
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
5307
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
5308
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
5309
+ "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
5310
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
5311
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
5312
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
5313
+ "mmlu_eval_accuracy_elementary_mathematics": 0.24390243902439024,
5314
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
5315
+ "mmlu_eval_accuracy_global_facts": 0.6,
5316
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
5317
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
5318
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5319
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
5320
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
5321
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
5322
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
5323
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
5324
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6153846153846154,
5325
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
5326
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
5327
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
5328
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
5329
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
5330
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
5331
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
5332
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
5333
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
5334
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
5335
+ "mmlu_eval_accuracy_machine_learning": 0.36363636363636365,
5336
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
5337
+ "mmlu_eval_accuracy_marketing": 0.8,
5338
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
5339
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
5340
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
5341
+ "mmlu_eval_accuracy_moral_scenarios": 0.26,
5342
+ "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
5343
+ "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
5344
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
5345
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
5346
+ "mmlu_eval_accuracy_professional_law": 0.3176470588235294,
5347
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
5348
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
5349
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
5350
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
5351
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
5352
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
5353
+ "mmlu_eval_accuracy_virology": 0.5,
5354
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
5355
+ "mmlu_loss": 1.2091298465551346,
5356
+ "step": 5600
5357
+ },
5358
+ {
5359
+ "epoch": 1.63,
5360
+ "learning_rate": 0.0002,
5361
+ "loss": 0.8971,
5362
+ "step": 5610
5363
+ },
5364
+ {
5365
+ "epoch": 1.64,
5366
+ "learning_rate": 0.0002,
5367
+ "loss": 0.8583,
5368
+ "step": 5620
5369
+ },
5370
+ {
5371
+ "epoch": 1.64,
5372
+ "learning_rate": 0.0002,
5373
+ "loss": 0.8893,
5374
+ "step": 5630
5375
+ },
5376
+ {
5377
+ "epoch": 1.64,
5378
+ "learning_rate": 0.0002,
5379
+ "loss": 0.8737,
5380
+ "step": 5640
5381
+ },
5382
+ {
5383
+ "epoch": 1.65,
5384
+ "learning_rate": 0.0002,
5385
+ "loss": 0.8117,
5386
+ "step": 5650
5387
+ },
5388
+ {
5389
+ "epoch": 1.65,
5390
+ "learning_rate": 0.0002,
5391
+ "loss": 0.8022,
5392
+ "step": 5660
5393
+ },
5394
+ {
5395
+ "epoch": 1.65,
5396
+ "learning_rate": 0.0002,
5397
+ "loss": 0.8379,
5398
+ "step": 5670
5399
+ },
5400
+ {
5401
+ "epoch": 1.65,
5402
+ "learning_rate": 0.0002,
5403
+ "loss": 0.8887,
5404
+ "step": 5680
5405
+ },
5406
+ {
5407
+ "epoch": 1.66,
5408
+ "learning_rate": 0.0002,
5409
+ "loss": 0.9023,
5410
+ "step": 5690
5411
+ },
5412
+ {
5413
+ "epoch": 1.66,
5414
+ "learning_rate": 0.0002,
5415
+ "loss": 0.8726,
5416
+ "step": 5700
5417
+ },
5418
+ {
5419
+ "epoch": 1.66,
5420
+ "learning_rate": 0.0002,
5421
+ "loss": 0.7458,
5422
+ "step": 5710
5423
+ },
5424
+ {
5425
+ "epoch": 1.67,
5426
+ "learning_rate": 0.0002,
5427
+ "loss": 0.8,
5428
+ "step": 5720
5429
+ },
5430
+ {
5431
+ "epoch": 1.67,
5432
+ "learning_rate": 0.0002,
5433
+ "loss": 0.8178,
5434
+ "step": 5730
5435
+ },
5436
+ {
5437
+ "epoch": 1.67,
5438
+ "learning_rate": 0.0002,
5439
+ "loss": 0.8373,
5440
+ "step": 5740
5441
+ },
5442
+ {
5443
+ "epoch": 1.67,
5444
+ "learning_rate": 0.0002,
5445
+ "loss": 0.8715,
5446
+ "step": 5750
5447
+ },
5448
+ {
5449
+ "epoch": 1.68,
5450
+ "learning_rate": 0.0002,
5451
+ "loss": 0.8141,
5452
+ "step": 5760
5453
+ },
5454
+ {
5455
+ "epoch": 1.68,
5456
+ "learning_rate": 0.0002,
5457
+ "loss": 0.821,
5458
+ "step": 5770
5459
+ },
5460
+ {
5461
+ "epoch": 1.68,
5462
+ "learning_rate": 0.0002,
5463
+ "loss": 0.8326,
5464
+ "step": 5780
5465
+ },
5466
+ {
5467
+ "epoch": 1.69,
5468
+ "learning_rate": 0.0002,
5469
+ "loss": 0.9078,
5470
+ "step": 5790
5471
+ },
5472
+ {
5473
+ "epoch": 1.69,
5474
+ "learning_rate": 0.0002,
5475
+ "loss": 0.8643,
5476
+ "step": 5800
5477
+ },
5478
+ {
5479
+ "epoch": 1.69,
5480
+ "eval_loss": 0.8042177557945251,
5481
+ "eval_runtime": 113.1516,
5482
+ "eval_samples_per_second": 8.838,
5483
+ "eval_steps_per_second": 4.419,
5484
+ "step": 5800
5485
+ },
5486
+ {
5487
+ "epoch": 1.69,
5488
+ "mmlu_eval_accuracy": 0.48645870209186454,
5489
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
5490
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
5491
+ "mmlu_eval_accuracy_astronomy": 0.5,
5492
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
5493
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
5494
+ "mmlu_eval_accuracy_college_biology": 0.5625,
5495
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
5496
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
5497
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
5498
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
5499
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
5500
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
5501
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
5502
+ "mmlu_eval_accuracy_econometrics": 0.25,
5503
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
5504
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
5505
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
5506
+ "mmlu_eval_accuracy_global_facts": 0.5,
5507
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
5508
+ "mmlu_eval_accuracy_high_school_chemistry": 0.22727272727272727,
5509
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5510
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
5511
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
5512
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
5513
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
5514
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
5515
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
5516
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
5517
+ "mmlu_eval_accuracy_high_school_psychology": 0.8333333333333334,
5518
+ "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
5519
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5520
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
5521
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
5522
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
5523
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
5524
+ "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
5525
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
5526
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
5527
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
5528
+ "mmlu_eval_accuracy_marketing": 0.84,
5529
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
5530
+ "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
5531
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
5532
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
5533
+ "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
5534
+ "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
5535
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
5536
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
5537
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
5538
+ "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
5539
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
5540
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
5541
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
5542
+ "mmlu_eval_accuracy_sociology": 0.5454545454545454,
5543
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
5544
+ "mmlu_eval_accuracy_virology": 0.5555555555555556,
5545
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
5546
+ "mmlu_loss": 1.3452752788913467,
5547
+ "step": 5800
5548
+ },
5549
+ {
5550
+ "epoch": 1.69,
5551
+ "learning_rate": 0.0002,
5552
+ "loss": 0.8273,
5553
+ "step": 5810
5554
+ },
5555
+ {
5556
+ "epoch": 1.69,
5557
+ "learning_rate": 0.0002,
5558
+ "loss": 0.8515,
5559
+ "step": 5820
5560
+ },
5561
+ {
5562
+ "epoch": 1.7,
5563
+ "learning_rate": 0.0002,
5564
+ "loss": 0.8425,
5565
+ "step": 5830
5566
+ },
5567
+ {
5568
+ "epoch": 1.7,
5569
+ "learning_rate": 0.0002,
5570
+ "loss": 0.8472,
5571
+ "step": 5840
5572
+ },
5573
+ {
5574
+ "epoch": 1.7,
5575
+ "learning_rate": 0.0002,
5576
+ "loss": 0.8045,
5577
+ "step": 5850
5578
+ },
5579
+ {
5580
+ "epoch": 1.71,
5581
+ "learning_rate": 0.0002,
5582
+ "loss": 0.8834,
5583
+ "step": 5860
5584
+ },
5585
+ {
5586
+ "epoch": 1.71,
5587
+ "learning_rate": 0.0002,
5588
+ "loss": 0.8467,
5589
+ "step": 5870
5590
+ },
5591
+ {
5592
+ "epoch": 1.71,
5593
+ "learning_rate": 0.0002,
5594
+ "loss": 0.9394,
5595
+ "step": 5880
5596
+ },
5597
+ {
5598
+ "epoch": 1.71,
5599
+ "learning_rate": 0.0002,
5600
+ "loss": 0.8009,
5601
+ "step": 5890
5602
+ },
5603
+ {
5604
+ "epoch": 1.72,
5605
+ "learning_rate": 0.0002,
5606
+ "loss": 0.8255,
5607
+ "step": 5900
5608
+ },
5609
+ {
5610
+ "epoch": 1.72,
5611
+ "learning_rate": 0.0002,
5612
+ "loss": 0.8928,
5613
+ "step": 5910
5614
+ },
5615
+ {
5616
+ "epoch": 1.72,
5617
+ "learning_rate": 0.0002,
5618
+ "loss": 0.8251,
5619
+ "step": 5920
5620
+ },
5621
+ {
5622
+ "epoch": 1.73,
5623
+ "learning_rate": 0.0002,
5624
+ "loss": 0.8334,
5625
+ "step": 5930
5626
+ },
5627
+ {
5628
+ "epoch": 1.73,
5629
+ "learning_rate": 0.0002,
5630
+ "loss": 0.8703,
5631
+ "step": 5940
5632
+ },
5633
+ {
5634
+ "epoch": 1.73,
5635
+ "learning_rate": 0.0002,
5636
+ "loss": 0.8593,
5637
+ "step": 5950
5638
+ },
5639
+ {
5640
+ "epoch": 1.74,
5641
+ "learning_rate": 0.0002,
5642
+ "loss": 0.7954,
5643
+ "step": 5960
5644
+ },
5645
+ {
5646
+ "epoch": 1.74,
5647
+ "learning_rate": 0.0002,
5648
+ "loss": 0.8163,
5649
+ "step": 5970
5650
+ },
5651
+ {
5652
+ "epoch": 1.74,
5653
+ "learning_rate": 0.0002,
5654
+ "loss": 0.8601,
5655
+ "step": 5980
5656
+ },
5657
+ {
5658
+ "epoch": 1.74,
5659
+ "learning_rate": 0.0002,
5660
+ "loss": 0.8204,
5661
+ "step": 5990
5662
+ },
5663
+ {
5664
+ "epoch": 1.75,
5665
+ "learning_rate": 0.0002,
5666
+ "loss": 0.7698,
5667
+ "step": 6000
5668
+ },
5669
+ {
5670
+ "epoch": 1.75,
5671
+ "eval_loss": 0.8051809668540955,
5672
+ "eval_runtime": 139.9971,
5673
+ "eval_samples_per_second": 7.143,
5674
+ "eval_steps_per_second": 3.572,
5675
+ "step": 6000
5676
+ },
5677
+ {
5678
+ "epoch": 1.75,
5679
+ "mmlu_eval_accuracy": 0.49011725445069554,
5680
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
5681
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
5682
+ "mmlu_eval_accuracy_astronomy": 0.5,
5683
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
5684
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
5685
+ "mmlu_eval_accuracy_college_biology": 0.5,
5686
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
5687
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
5688
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
5689
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
5690
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
5691
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
5692
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
5693
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
5694
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
5695
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
5696
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
5697
+ "mmlu_eval_accuracy_global_facts": 0.6,
5698
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
5699
+ "mmlu_eval_accuracy_high_school_chemistry": 0.2727272727272727,
5700
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5701
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
5702
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
5703
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
5704
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
5705
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
5706
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
5707
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
5708
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
5709
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
5710
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5711
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
5712
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
5713
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
5714
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
5715
+ "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
5716
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
5717
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
5718
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
5719
+ "mmlu_eval_accuracy_marketing": 0.8,
5720
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
5721
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
5722
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
5723
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
5724
+ "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
5725
+ "mmlu_eval_accuracy_philosophy": 0.4411764705882353,
5726
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
5727
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
5728
+ "mmlu_eval_accuracy_professional_law": 0.3411764705882353,
5729
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
5730
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
5731
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
5732
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
5733
+ "mmlu_eval_accuracy_sociology": 0.5454545454545454,
5734
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
5735
+ "mmlu_eval_accuracy_virology": 0.5,
5736
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
5737
+ "mmlu_loss": 1.4094214880201898,
5738
+ "step": 6000
5739
  }
5740
  ],
5741
  "max_steps": 10000,
5742
  "num_train_epochs": 3,
5743
+ "total_flos": 1.6162883060541358e+18,
5744
  "trial_name": null,
5745
  "trial_params": null
5746
  }
{checkpoint-4000 → checkpoint-6000}/training_args.bin RENAMED
File without changes